{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Disaggregation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import print_function, division\n",
    "import time\n",
    "\n",
    "from matplotlib import rcParams\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from six import iteritems\n",
    "\n",
    "from nilmtk import DataSet, TimeFrame, MeterGroup, HDFDataStore\n",
    "from nilmtk.legacy.disaggregate import CombinatorialOptimisation, FHMM\n",
    "import nilmtk.utils\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "rcParams['figure.figsize'] = (13, 6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dividing data into train and test set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = DataSet('/data/redd.h5')\n",
    "test = DataSet('/data/redd.h5')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us use building 1 for demo purposes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "building = 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's split data at April 30th"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.set_window(end=\"2011-04-30\")\n",
    "test.set_window(start=\"2011-04-30\")\n",
    "\n",
    "train_elec = train.buildings[1].elec\n",
    "test_elec = test.buildings[1].elec"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading data for meter ElecMeterID(instance=4, building=1, dataset='REDD')     \n",
      "Done loading data all meters for this chunk.\n",
      "Loading data for meter ElecMeterID(instance=20, building=1, dataset='REDD')     \n",
      "Done loading data all meters for this chunk.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x21f6e9b99e8>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_elec.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x21f704a6e80>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_elec.mains().plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "REDD data set has got appliance level data sampled every 3 or 4 seconds and mains data sampled every 1 second. Let us verify the same."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "fridge_meter = train_elec['fridge']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "fridge_df = next(fridge_meter.load())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>physical_quantity</th>\n",
       "      <th>power</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>type</th>\n",
       "      <th>active</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-04-18 09:22:13-04:00</th>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-18 09:22:16-04:00</th>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-18 09:22:20-04:00</th>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-18 09:22:23-04:00</th>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-18 09:22:26-04:00</th>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "physical_quantity          power\n",
       "type                      active\n",
       "2011-04-18 09:22:13-04:00    6.0\n",
       "2011-04-18 09:22:16-04:00    6.0\n",
       "2011-04-18 09:22:20-04:00    6.0\n",
       "2011-04-18 09:22:23-04:00    6.0\n",
       "2011-04-18 09:22:26-04:00    6.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fridge_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "mains = train_elec.mains()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading data for meter ElecMeterID(instance=2, building=1, dataset='REDD')     \n",
      "Done loading data all meters for this chunk.\n"
     ]
    }
   ],
   "source": [
    "mains_df = next(mains.load())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>physical_quantity</th>\n",
       "      <th>power</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>type</th>\n",
       "      <th>apparent</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
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       "      <th>2011-04-18 09:22:09-04:00</th>\n",
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       "      <th>2011-04-18 09:22:10-04:00</th>\n",
       "      <td>344.559998</td>\n",
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       "    <tr>\n",
       "      <th>2011-04-18 09:22:11-04:00</th>\n",
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       "      <th>2011-04-18 09:22:12-04:00</th>\n",
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       "      <th>2011-04-18 09:22:13-04:00</th>\n",
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      "text/plain": [
       "physical_quantity               power\n",
       "type                         apparent\n",
       "2011-04-18 09:22:09-04:00  342.820007\n",
       "2011-04-18 09:22:10-04:00  344.559998\n",
       "2011-04-18 09:22:11-04:00  345.140015\n",
       "2011-04-18 09:22:12-04:00  341.679993\n",
       "2011-04-18 09:22:13-04:00  341.029999"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mains_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since, both of these are sampled at different frequencies, we will downsample both to 1 minute resolution. We will also select the top-5 appliances in terms of energy consumption and use them for training our FHMM and CO models."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Selecting top-5 appliances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15/16 MeterGroup(meters==19, building=1, dataset='REDD', appliances=[Appliance(type='unknown', instance=2)])e=1)])ce=1)])\n",
      "  ElecMeter(instance=3, building=1, dataset='REDD', appliances=[Appliance(type='electric oven', instance=1)])\n",
      "  ElecMeter(instance=4, building=1, dataset='REDD', appliances=[Appliance(type='electric oven', instance=1)])\n",
      "16/16 MeterGroup(meters= for ElecMeterID(instance=4, building=1, dataset='REDD') ...   \n",
      "  ElecMeter(instance=10, building=1, dataset='REDD', appliances=[Appliance(type='washer dryer', instance=1)])\n",
      "  ElecMeter(instance=20, building=1, dataset='REDD', appliances=[Appliance(type='washer dryer', instance=1)])\n",
      "Calculating total_energy for ElecMeterID(instance=20, building=1, dataset='REDD') ...   "
     ]
    }
   ],
   "source": [
    "top_5_train_elec = train_elec.submeters().select_top_k(k=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MeterGroup(meters=\n",
       "  ElecMeter(instance=8, building=1, dataset='REDD', appliances=[Appliance(type='sockets', instance=2)])\n",
       "  ElecMeter(instance=5, building=1, dataset='REDD', appliances=[Appliance(type='fridge', instance=1)])\n",
       "  ElecMeter(instance=9, building=1, dataset='REDD', appliances=[Appliance(type='light', instance=1)])\n",
       "  ElecMeter(instance=6, building=1, dataset='REDD', appliances=[Appliance(type='dish washer', instance=1)])\n",
       "  ElecMeter(instance=11, building=1, dataset='REDD', appliances=[Appliance(type='microwave', instance=1)])\n",
       ")"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_5_train_elec"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Training and disaggregation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### A function to disaggregate the mains data to constituent appliances and return the predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict(clf, test_elec, sample_period, timezone):\n",
    "    pred = {}\n",
    "    gt= {}\n",
    "    \n",
    "    # \"ac_type\" varies according to the dataset used. \n",
    "    # Make sure to use the correct ac_type before using the default parameters in this code.    \n",
    "    for i, chunk in enumerate(test_elec.mains().load(physical_quantity = 'power', ac_type = 'apparent', sample_period=sample_period)):\n",
    "        chunk_drop_na = chunk.dropna()\n",
    "        pred[i] = clf.disaggregate_chunk(chunk_drop_na)\n",
    "        gt[i]={}\n",
    "\n",
    "        for meter in test_elec.submeters().meters:\n",
    "            # Only use the meters that we trained on (this saves time!)    \n",
    "            gt[i][meter] = next(meter.load(physical_quantity = 'power', ac_type = 'active', sample_period=sample_period))\n",
    "        gt[i] = pd.DataFrame({k:v.squeeze() for k,v in iteritems(gt[i]) if len(v)}, index=next(iter(gt[i].values())).index).dropna()\n",
    "        \n",
    "    # If everything can fit in memory\n",
    "    gt_overall = pd.concat(gt)\n",
    "    gt_overall.index = gt_overall.index.droplevel()\n",
    "    pred_overall = pd.concat(pred)\n",
    "    pred_overall.index = pred_overall.index.droplevel()\n",
    "\n",
    "    # Having the same order of columns\n",
    "    gt_overall = gt_overall[pred_overall.columns]\n",
    "    \n",
    "    #Intersection of index\n",
    "    gt_index_utc = gt_overall.index.tz_convert(\"UTC\")\n",
    "    pred_index_utc = pred_overall.index.tz_convert(\"UTC\")\n",
    "    common_index_utc = gt_index_utc.intersection(pred_index_utc)\n",
    "    \n",
    "    common_index_local = common_index_utc.tz_convert(timezone)\n",
    "    gt_overall = gt_overall.loc[common_index_local]\n",
    "    pred_overall = pred_overall.loc[common_index_local]\n",
    "    appliance_labels = [m for m in gt_overall.columns.values]\n",
    "    gt_overall.columns = appliance_labels\n",
    "    pred_overall.columns = appliance_labels\n",
    "    return gt_overall, pred_overall"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Train using 2 benchmarking algorithms -  Combinatorial Optimisation (CO) and Factorial Hidden Markov Model (FHMM)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "********************\n",
      "CO\n",
      "********************\n",
      "Training model for submeter 'ElecMeter(instance=8, building=1, dataset='REDD', appliances=[Appliance(type='sockets', instance=2)])'\n",
      "Training model for submeter 'ElecMeter(instance=5, building=1, dataset='REDD', appliances=[Appliance(type='fridge', instance=1)])'\n",
      "Training model for submeter 'ElecMeter(instance=9, building=1, dataset='REDD', appliances=[Appliance(type='light', instance=1)])'\n",
      "Training model for submeter 'ElecMeter(instance=6, building=1, dataset='REDD', appliances=[Appliance(type='dish washer', instance=1)])'\n",
      "Training model for submeter 'ElecMeter(instance=11, building=1, dataset='REDD', appliances=[Appliance(type='microwave', instance=1)])'\n",
      "Done training!\n",
      "Runtime = 1.5623564720153809 seconds.\n",
      "Loading data for meter ElecMeterID(instance=2, building=1, dataset='REDD')     \n",
      "Done loading data all meters for this chunk.\n",
      "Estimating power demand for 'ElecMeter(instance=8, building=1, dataset='REDD', appliances=[Appliance(type='sockets', instance=2)])'\n",
      "Estimating power demand for 'ElecMeter(instance=5, building=1, dataset='REDD', appliances=[Appliance(type='fridge', instance=1)])'\n",
      "Estimating power demand for 'ElecMeter(instance=9, building=1, dataset='REDD', appliances=[Appliance(type='light', instance=1)])'\n",
      "Estimating power demand for 'ElecMeter(instance=6, building=1, dataset='REDD', appliances=[Appliance(type='dish washer', instance=1)])'\n",
      "Estimating power demand for 'ElecMeter(instance=11, building=1, dataset='REDD', appliances=[Appliance(type='microwave', instance=1)])'\n",
      "Loading data for meter ElecMeterID(instance=4, building=1, dataset='REDD')     \n",
      "Done loading data all meters for this chunk.\n",
      "Loading data for meter ElecMeterID(instance=20, building=1, dataset='REDD')     \n",
      "Done loading data all meters for this chunk.\n",
      "********************\n",
      "FHMM\n",
      "********************\n",
      "Training model for submeter 'ElecMeter(instance=8, building=1, dataset='REDD', appliances=[Appliance(type='sockets', instance=2)])' with 3 states\n",
      "Training model for submeter 'ElecMeter(instance=5, building=1, dataset='REDD', appliances=[Appliance(type='fridge', instance=1)])' with 3 states\n",
      "Training model for submeter 'ElecMeter(instance=9, building=1, dataset='REDD', appliances=[Appliance(type='light', instance=1)])' with 3 states\n",
      "Training model for submeter 'ElecMeter(instance=6, building=1, dataset='REDD', appliances=[Appliance(type='dish washer', instance=1)])' with 3 states\n",
      "Training model for submeter 'ElecMeter(instance=11, building=1, dataset='REDD', appliances=[Appliance(type='microwave', instance=1)])' with 3 states\n",
      "Runtime = 2.2812917232513428 seconds.\n",
      "Loading data for meter ElecMeterID(instance=2, building=1, dataset='REDD')     \n",
      "Done loading data all meters for this chunk.\n",
      "Loading data for meter ElecMeterID(instance=4, building=1, dataset='REDD')     \n",
      "Done loading data all meters for this chunk.\n",
      "Loading data for meter ElecMeterID(instance=20, building=1, dataset='REDD')     \n",
      "Done loading data all meters for this chunk.\n"
     ]
    }
   ],
   "source": [
    "classifiers = {'CO':CombinatorialOptimisation(), 'FHMM':FHMM()}\n",
    "predictions = {}\n",
    "sample_period = 120\n",
    "for clf_name, clf in classifiers.items():\n",
    "    print(\"*\"*20)\n",
    "    print(clf_name)\n",
    "    print(\"*\" *20)\n",
    "    start = time.time()\n",
    "    # Note that we have given the sample period to downsample the data to 1 minute. \n",
    "    # If instead of top_5 we wanted to train on all appliance, we would write \n",
    "    # fhmm.train(train_elec, sample_period=60)\n",
    "    clf.train(top_5_train_elec, sample_period=sample_period)\n",
    "    end = time.time()\n",
    "    print(\"Runtime =\", end-start, \"seconds.\")\n",
    "    gt, predictions[clf_name] = predict(clf, test_elec, sample_period, train.metadata['timezone'])\n",
    "   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using prettier labels!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "appliance_labels = [m.label() for m in gt.columns.values]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "gt.columns = appliance_labels\n",
    "predictions['CO'].columns = appliance_labels\n",
    "predictions['FHMM'].columns = appliance_labels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Taking a look at the ground truth of top 5 appliance power consumption"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "                             Sockets    Fridge      Light  Dish washer  \\\n",
       "2011-04-30 00:00:00-04:00  30.566668  6.000000  76.133331  1132.033325   \n",
       "2011-04-30 00:02:00-04:00  28.551723  6.000000  76.206894  1131.517212   \n",
       "2011-04-30 00:04:00-04:00  28.233334  6.000000  76.099998  1132.066650   \n",
       "2011-04-30 00:06:00-04:00  28.500000  6.100000  76.900002  1038.866699   \n",
       "2011-04-30 00:08:00-04:00  24.193548  6.612903  81.032257   205.387100   \n",
       "\n",
       "                           Microwave  \n",
       "2011-04-30 00:00:00-04:00        4.0  \n",
       "2011-04-30 00:02:00-04:00        4.0  \n",
       "2011-04-30 00:04:00-04:00        4.0  \n",
       "2011-04-30 00:06:00-04:00        4.0  \n",
       "2011-04-30 00:08:00-04:00        4.0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
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   "outputs": [
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       "                           Sockets  Fridge  Light  Dish washer  Microwave\n",
       "2011-04-30 00:00:00-04:00      0.0     0.0    0.0          0.0     1306.0\n",
       "2011-04-30 00:02:00-04:00      0.0     0.0    0.0          0.0     1306.0\n",
       "2011-04-30 00:04:00-04:00      0.0     0.0    0.0          0.0     1306.0\n",
       "2011-04-30 00:06:00-04:00     71.0    65.0    0.0       1069.0        0.0\n",
       "2011-04-30 00:08:00-04:00     71.0     0.0   81.0        221.0        0.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions['CO'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
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   "outputs": [
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-04-30 00:00:00-04:00</th>\n",
       "      <td>22.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1359.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-30 00:02:00-04:00</th>\n",
       "      <td>41.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-30 00:04:00-04:00</th>\n",
       "      <td>41.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-30 00:06:00-04:00</th>\n",
       "      <td>41.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-30 00:08:00-04:00</th>\n",
       "      <td>41.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Sockets  Fridge  Light  Dish washer  Microwave\n",
       "2011-04-30 00:00:00-04:00     22.0     6.0   81.0          0.0     1359.0\n",
       "2011-04-30 00:02:00-04:00     41.0     6.0   81.0       1068.0      111.0\n",
       "2011-04-30 00:04:00-04:00     41.0     6.0   81.0       1068.0      111.0\n",
       "2011-04-30 00:06:00-04:00     41.0     6.0   81.0       1068.0        4.0\n",
       "2011-04-30 00:08:00-04:00     41.0   192.0   81.0         47.0        4.0"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions['FHMM'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting the predictions against the actual usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x21f7054d278>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "predictions['CO']['Fridge'].head(300).plot(label=\"Pred\")\n",
    "gt['Fridge'].head(300).plot(label=\"GT\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x21f6e7016d8>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PXnffP+CXDy3Htc5TBr7+wKPbcNfGLa0tHq6/9xF86se34Gl77YhjnxxIIuMxnQnWb1rE5356K3687Hl4Lr6B5fJRnO6/BFff6+Pn4mk46OFL8JHFEyGLOtoNcOeGLdh1hyVh8XDXxi344s9ux6oV3ahwaik9T+K+R7bh6CetxgkHqWvxF7dvwHlX3I3H77AEHbe8OOfxUiWN3baxh/9+cAMe3LSIk569N/bbZQUA4HvX3ocLr74X1+18Kj4jbsdr134Mr5Afx1V37WaLh2lHSsaSjsBP/+J5pR5/4VVr8e7zf42+L4sfDMAPOhplHz94csOt4L7HePHBu+Gg3XfAh751fdQx6SzF2Wv+Dm+4/q34DP0D8OaLVVs/4L9uXo+Tv/DL8uct1XE/+oqDcMJBuwIAfnzTOvzhl341cIyep/79k/ccHXZi3n/htbj4hjmKkA2Kh2esWYX3v6ncdQQAeOQQ4N+PxZfwcaUL3v/5A1++9+GtOOLvLwXPgBZyWpDM2B5b0IWHE5/3TJx4RInna9PTgX8/Bp/3/gl4yyXAjsOF3LeuuQfvOPca9EZ5nVtSYelDQgy8t2TzPODnq/G7P3w/Ll1zFvCqf1eRoQE9T+KJ/+f76Pv2tWQc6UOAsXr7FfjpewpeT1ufCXzhePy/Tf8I/OHFwKqoGH/zmb/C+sfau3Mt0+71aZ6HAH0tvvmFR6Cz8VRg3W/wL2/4M+WJuG4j8I0348evXgD2Oar2c6/KgR/6wcDvqf/9kZcd1NriT3PT/Y/hBf9yGWTsrUKvh85+y7Ox7+oV5Q+2/ibg08AHXvZUPANPwalfuWpw/eQzuq7Aj957ArB+H+D0o3FG9wy8qf9+U7/ORJkrz4MvGSJvWyuBluvoRXMRMrjoyj5+8JuHi4eeL9F1BSg4Zz+2sNzk7IB3uh9Qbz5f+T1g/W+j83Yqnndw3Pg9eyHlGD1fouPQwM2diMLfey4IigfKM0ynscPuwEnfADrLgK/+HnDuSSp+N0Bfl3Y9ag5fAqsp2B3NMkwnWbEaeP3Xgf5WFaN458+HHrJQ8X3BUgLpQ5IoJQ8FABz+NuD4jwG/+RZw/skDCSYdRx1j0T4/5pGe+uiU2HdcupOKQxYucParBpKyuo5o9etHv08PXGM5siX9u3ZdoaZPn/zNKO77iSeo+8K159Z5yiPTdQefq4HfpeXotxs/toaJ1kMVJamxtKW0tWPPk+G6CqufBLzw49h/81U4uf/10U6+Ydr/7FdAMuBUuCA6egFdckWXuhtR6hslAE7pPEh0HBGec3xTWkrgPvF44MTzgM3rgU8/C/j6m4B1N4attqrnHddv62PEd+/0+cRxiCp5SFpPWcN0GrseBLzt58CxHwZuvRQ488XAY/cDiIJm5upvWTOSGavwqPqfPMN0kl0OUIUe+2o44/f/EvCiXVL9Ghipw2hJJ+g8VOKI04AXfwL47Q+Ac6IZOESEriPs81MH2hSajGrNYud9gDd8A+hvBr54fDiro+O2+/mJ7vXxLets2ZL+XZP3TwBAdzlwyEnANecA6240fq7j0nEEerHfsxf+Lu33e+nNivh9V1s6q6wVAQwUD2n3iL4vB2VQTzsZ1+50PE7l84FvnaY2rFrEnBUPnKunTdJ1hhfQeejqtVe1Xa53cxKeh54v0XVEanXsM6vP7/lM4B2/Bo58J3DzRcBnj8CeV/wdlmIb+iV3dvRx45V25sWfePMTNHhesw7r56pq50HjLgBHvRv4g2+pgTFnvRzYvCH829viwRxScvXOg2avZwN/8nPgWW8FfvG5gfkqtnioAfbBoxTkz3wL8IrPqrz8r/wesE0Vix2HSr//WSogKxYPAPD4pwF/dBHQXQF8+SXA9d9Ex6FWy/50t33gPSA5XTiG3oFOLR4AlVDVXQH88K+mLsYzWYjr11U363dpEWn3Xa3wqFo7xNOW0jae+4FyI4QI393vw/isfKVK+vvC8cDG26v/Eg3R/me/ApK5UjpKp7L8R32sfNMKi4dE5yFYrKdWx8xRi3/5KuD5fw2841rgkNdj9bWfxw+7fwkObqRlzzsuGdAXeS+h2RsqHgRN23tdrchgW4KyMunLsuezgNefp2L6vvRCLLntIgA8XxKwmpEMrKJH1P8s36X6ARZWAC/6R+AFfwvc8G3gO+8CmCt3JC0lYB886u3okNerWOS1v1KL0/U3tX5ne2rxK8iW4qzcVxUQj3sK8PU34dX3/zPIa++wrPBeP+B5yJYt6cdlLriXrwSO/kvg1kuAm39k8lTHpuNQYhNR/fJVzMTTiu4uxAMkOUWJUYrUzkOsY5Oi3HBdF//kvUbJ+x6+C/j87wI3fq/ib9EM7X/2KzCq56HsTUgv7isvKlKKB8+XkKzOQaRc4DLtd1m+Enj5p7D+mE9gL7EeSx4q1wJN9TxkafbcZOeBBrwYs46vn1sTqRj7HAWceC7gbcOKC0/Ct7ofxNIt9xZ/n6UUPqvOA5Or9NejcvifAke+G7jqy8D5J2P1vZdiAb1Wa7anDilH6zxoDnoV8NqvAg/dCXzuSJyKC+DN45Tjugk6D5SVZZ/Hdo8D/vD7wBFvx+Eb/wPv63/G8MlNDn3PG3gPyJEtlfIJPPOtwMr9VPdhiuaYDHkefNWBnYXOg15Cxdcw+hY/juchdf0UeFjjdB0HvmT4+x0P/PFPgZ3XAOeeCFz811GhPqW0/9mvgGSUN+Qhffc9//ijeh6Gi4ewuncE9Gt0sPOQXRnzzkHyUm9LuR8fbKM4pWRLgz/TEfPleQhlS+N2HjT7Pg/4syux7fl/i6eK27Drxl+aOa4Fkhmr8Qj6S1eO/3wd+yHgqPcAt1+G/S55C3628HbIbY+ZOVFLIFsa8zl60gnAab8CDngJTpXn4nc2TNcO7kzg6+JhxKBGpwMc/ze4Ycej8WS+1eCJTZbUjUK/nynnit/PM3G7qtP50B3AGc8D1t1g6nTHopOQLfW8Er9LS9BrKE6oOoARbhkpsqXk+ilZcHVcih630xrgzT8CnvEm4L//GTj7FUraPKW0/9mvgNqtL//48AKo6B2ovCMZaKnjnoe4KUmkpC35Of4Nd0kQL9YvVzxEGr/qngeiwY7IrCNTnquxcTqQB7w0+AHTvdvQJqRkrKJH4C2tYJbOggg49oPAe27Bg894B1bRo6AtG8Y/rgUAQKN6HpKs2AV4+acBAEt7G8c/nmWQMG0pZ5JyCTYteRxW4yEDJ9QMoefBSxqm82VLhSbjfY8B3vgdYHETcMaxahJ1wzvQScN0KMFyZ8AwnZJyOHbakuiEz3NS7pVcP3WTEtjOEuCl/wq84nPA2iuAzz0HuPRjqqCcMuareGCu5KDvVkwt4lAHOaphOt55iNqcgoarY875XZyFasWDPuxA2lJ4UQ++acx72pIuHipHtRYggpsOyWpTLS3ZSFZRrf6yEfwOWbhd+Dupzp6vd5os42Oi86DR76PSPj/GCe5VI8mWYmzrrsJ2tBW8uMnEWU2cdM9DjmwpL20pyd6HA398mTKaf/fdwGeercJQGqLriIEN1NzkqJaRlnKYpsQoRdh56Kb6ZZXnYfCYmRvUh5wIvOViYNeDgcv+EfjXp6pEppJqkknQ/me/Amq3vkLxUDFVZfTOw3Dx0IslGqRVx3n+jc7S5QAACqILi4jSlqLPpeUUL3rDmr158zzI0PNg9qUTygDYdh5M4UvGKnoU3tJVRo/rOmqHvO/Z58oUJKW5bp5e2NrizjzB31S4YxYPQTfQe/T+sU+pCaJkxfhN2Sv0PCQ9g5lsvxvwpu8ArztH/f95b2jseu66YjA4ZabmPKSlLQ1+rTSh56ETeR4GAmdSPA95G9S7HgScfCHwruuAI/4MuPorwL8fCzx4c7Xzqon2P/sV4ByfQBrhrAOv3OLYrOchqu6zPA9Z/g13yXbqcF5Jz0Oo8YuOl1Y4pWn2dNrSvExGZt15MClbAuAExQNZ2ZIxWPpYhUfgLzcgW4rhuOq58m3xYAyCbyaEAACI4EPYQrwG2B/DMB1jcYnqBvqP3Df2OTUBZxqmi2RLFZZcRMABLwKO+nPA26bSeBpgOG1pdjoPUdrSoKoDGMXzkJK2lOjYJP9m0eNy1k877AEc/1HgDRcAm9apePcpoP3PfgX8yp6HSRmmtY4+pXiIT5iWg621rN+lsyToPHjlho6kafxCzd7Axc+hwUejz2FeEkZloD+tS7YEK1syhlh8GB3yIZcZLh4cWzyYhliaky0B8OHYQrwG/CDBSoxqmA7oLVXFg2xr5yF5r2cuNyRulN36nZ+gPm5oxmDecZJpS7NjmI78pNHn0uZelSIuW0obsptmmK6yxtzvWOCZfwQ8es9UzAJp/7NfgYHZCCXopujW8o+vPo4e1RozTAeVaDdrwnTOzApyu+ixA1FyYmHaREVHEIgw1K5MXvxOSttvlmH9JDtmOw+hDMDulhqju+1BAIA06XmAyuYGAG/Ko/TaBLFB2RIAn1wrW6qBfl8XD+MZpr1lamij/2g7o6nDe71eG0gfAGd2HvSCe6R4U52euLGh4iFLtjQLxUPwK3BC1QGMMuchSlsaMkIjWD8liseFiuMAwg1mbj6lpv3PfgUk1zvnwajnIZZooC9wP6HLy/NvbMUSOH7VtKXoc0SEriNSJiQOy5aA+ZkyLWU9nQf93FvDtDlE4Pnhhe2MHlcXD75vnytTEBuULUEVD8T2+TGNr4uHMT0PWLIjFrkz1VGUeQxNmI7p3dMYa8G9fBWwsH1jnYeF5ITpWJhL2xFpqo6RJ0zHZUtBRyGp3MiQLZVeM+oNlinoqrb/2a+AlNUc9GlxpXlwTZ6HNFOPSlvKPuQ2WoBbUraUNVFRpSzEJiT6cqjtKlK6IrMMcz1pS9qAbaUW5tAzOYThLpEjrGzJNKY7D9LKlmpBD94T7nidh05HYD12AG1qafEQ3uuDG19s4ZhGJFsaId6USEmXmuo8JNYBfV9C0Ag781OI/h3ie58m0paIaMgrkjZhuuoaM0qSa35jZK6Kh7zZCGm4QuvRyq2MfZl4QylLmufBSykeYld40bTsbVgC1y9XPGRNVOy4wzsOQ4bplAmNs0yYtiTG0/wOQYQ+O1a2ZBAO9Hhk+LnSem/fypaMIUwapgFIckFsZUum8Tz1N3XG7Dx0HIEHeCeIze0sHobSlgrmX8Tv5yOxcl9g422jfe+YdNzEIjhFgdBW9JJnMG1pnDkPFG6CDA3X8+XQbIxOirwpl7B4aP7eMxtXQEk4xyeQRijdmZTnwUmTLYn06rjAv7GVlsApWTzIsPMw+PmOQ0M5xUOeBzHcFZllorQl8y8dHwLCSi3MwTU9V8HxbOfBHMTSaIKZFC7EFNxgZw0tW3I64xUPXUdgHe8Isamdhml9uwvvjwWypb4vQRRtSFZm531V2lLQ+ZkkQ4bplHVAW0lLW9L/rOKPBRAZ5oNjdl2RkC0N/926KcbqXGzx0AxFu/VpdBO773nItPi2Ut+YP+dBn/Jg2hJyk6MWaQm6JT0PkcYvIVsa6jwMpy1RyotvlpF6N9u0bAkqIWYa2pGzgi70hOFYXb1DLm3nwRgCcoRsxGyk9TzUgh92HhbGOk7HVcWDu2WdidOaOENpSwWypcVgt77KnKkBdn6CMsk+fOdo3z8GyTkP/ZR5BW0lSlsql2SZi98feP6HJnOnyJaqhvKE86WmYJ0wsSuAiL5IROuI6LrY584jomuC/+4gomuCz68hoq2xr33OxDnkzUbIIqlbyz++Sc9DFIcWpS0Nmnryuig9sQQdua3cj+d0jV8naZhOufidsO1X6ke1Hq2jNz3nAQB8ciCsbMkYHCRSCNMSs+C5t4ZpcwjDnQe2r6VaCDsP7nivKdV52Alu7xGgX+4+NU0M3eu13l1kdB48Hm+3fmWQuNSAabqbNEx7w8bftiIyVB0j+TkScz6G/m4+D3lG9WZsdc9D8+9thu+quZwJ4FMAztKfYObX6n8T0ScAPBJ7/K3MfIjJE1BpS9W+J6lby0M/zKxhmqJEo4QuL6+LskhL0JUPlvrxWZ6H5MXfyxgSp44xH9WD1tGb3CXVeBA2bckkenFv+rnSnYcpeAOfFQQkQOZuR1K4cOzzYxzpadnSmIZpR94emTAAACAASURBVGAddlT/s+kBYKe9xz21iSJDz0PSMJ0tW+rkJZwU0WBca8cRkKzu8Y5Qm6kjGb+nFEEJPynzaB2iRPEQ33hm5lSvyOiG6ebf2yZWPjLzZQA2pn2N1DP1GgDn1HkOkrmyg77jCCyW9jwEuxElJ1JH35gy5yHmeYjSluI/K9/Q03eWolux85BcY8W1jvriT7YrRUpXZJapbTcbwWArK7Uwhk7GGneg1RC68+DZ58oEzAwB32gqlpUt1YOWLbljpi11XdV5AAA81j7fw9CchxJpS2NJfZbtDCzZoRHTdDJOdDFlEdxmHEGJJMsRkpaAIdlS3POglSQL7piypXksHgo4CsADzHxz7HP7ENHVRPRTIjrKxA9RPoFqF8WCK0qbWXT1umig8xD3PERTnMvr8nqifPHAGekC3djv7ksG83BaRFphM8tEE6bN77yo4qH5N4WZISz0avI8TMEb+CzgS4YDs1GtEC4ceHOzqTEppC4eOmN6HhzCOtadhzYWD0nZUn7aUlpMZyWIVPehCdmSO5gI1J8hwzSg7uXJqNbRPA/JzkOk3IgrSeIk/7aF2CFxQ5yIwa7DfQD2YuanAXg3gK8R0fZp30hEpxDRFUR0xfr163N/iM9cWcGgMo6rpS2VfXz0jflzHsJEo8QgkzxdnieWYIHLFQ/6uk0er+NQ9IaRMZJe/++8RLVG8Z/mPQ8Sjk1bMkhtyVjB8dgapo3Q9xkCbNbzIFy47M+NnHJSSF8XD2N2HoK0JQCtHBQXxbKXHBKXIvmtTEOzHrrOoC5/lgzTgOoyJKNaKyctAYDMNkzH13NxQtmSHRJXHSJyAbwKwHn6c8y8yMwbgn9fCeBWAE9M+35mPp2ZD2XmQ1evXp37s7jihGlgOOM4j6EEhrLkFQ8ZsiVf5uvy+s5SLKBXypWfNVExXjn3MirneUtbihakNRim4VjPg0lkTbKlsPNgnysT9HwJB4YN06IDl/zqM3csuUTFw/hzHjZiO0hyW9l54ORGYQnZ0thSn5X7Ao+sBbzF8Y5TkaQuP21ScptJeh64QBKeid8fNkwH10cvY85HJyzMyka12uIhzvMB3MjMa/UniGg1kbpDE9ETAOwPYGyxnzb8VCGZOJTH6BOmU4bEBRdTNzYkzpfldXm+szQ4UHFca1baUnzGhf6Y1OyFOclz13moIaqVhJUtGST0p5iO1Q3TluxzZYKep4oHo/Iy4cCFXz0225KLNkx3xu08uAIMgW0LK1vpedAbheHaIJwunGWY5vF363feV8lVHrpjvONUJOl5UBKsGTJMCxoMoxlhnai+sTfseUhsviavgZFlS/NUPBDROQB+DuBJRLSWiP4o+NLrMGyUfi6Aa4no1wC+AeBUZk41W1dBcnWterUhcePOeYhunotetNOv16k81FrLPqTnBsVDr0TxIPM8D0nNXjJtKTjGfNQOkFpWVFPnwcqWDKK7RAaNuMEB1eGlXZiaoO9LCEizHSLRUcVD1Y0cSy4cLJLHLR70fWTLwupWFg9D9/oi2ZKJBXdDca3RILNoIdx1zd//mkIQIb73OUoqJ4Ch4iGethTfDI7TEe01TE8sqpWZT8z4/JtSPncBgAtMn4NKW6r2PV1XYPNiuSdK36d6VVvlGbKljkMgonB3f2CQSYEEy3eWBQfaXHzeGRMVlWwpX7OX1hWZaeoaPAZAkk1bMkpdsqXguWc758EI/RpkS3BcuPCrd4EtuZgqHvQianNnFVZtap/nQYaeh+C+J3XnIcMwbUK2tP3j1cfH7hvvOBWJOg/RWqA7Q50HR9DgAN4R5O0AhmRL8bTK7M1XgivKS+Mj2VLz955pkC1NjFEuisnIllKKh1g6A6VFtRZMy/bdoHgo0XmI0pYGP5968c95VKvebTYuhYHtPBintrSlwDA9Bbs/s0Df8yGIDXcebPFQB+z30WcHnTF3nvWcgM3ddsqWwnCUIdlSTVGtQGNJO93EIDMj/o0pQlAyyXJUz0Oi8xBTbvRiSpIkVWaJRZ2H5tcJs3MFlMCXI06YLjm3QVev1WVLw56H+EyF9LSl4XSkgUN2dOehuHjQ5508XteN0pYWY9GxcZyUAXYzTV1SGKi0Jet5MAeHXaJ6PA/WMG2Gxb5aeJn1PHSs56EG2O/DgzN2cpD+/kfdVcCWB4HAS9EW9D3Tk6zuyyVkS2OnLQVyyUkXD2HnIbYQnq3iYThtyYTnYcEp9jzoz7VRtjQ7V0AJeAQtW9d1SleFQ7sRZUnxPMSr+7Q5DyptKfuQHHYeimVL+rzzJkyHmr3EZMnw3ObkHl2vYdp2HkyiJWBkeqBfcBNnWzwYwfPU+5/JIXHkWM9DLfge+nDG3kV3BIEIeKyzUn1i8zoDJzc54p32ni8nk7YUGgwn+76ji56+F60FZimqVRANrF8k56+tMkmRLemN537G5qt+XGmpO9m0pUYYLW2JSt+A9OI+3I0oS+qQOA4vtPS0pfxp2bKrDdNliod0w3R8xkWR52Fu0pZqnDAtbfFgFP1coaa0Jet5MENUPJh7TZHj2qjWOgg6D+Oaf4kIHUfgURHMetiywcDJTY54p73vy0i2JLLTlpKS38qEnYfJvu90EolARvwbU4STSFuS46QtxZ7/eMx/L0P2Dag5Gla2NOWoirL+tCUA6FfZis8wTOvqXkut4utzv8C/QZ3l6nvKFA8yw/MQmzCdVTnPW/GAugaPwXoejKOLh5omTE/DG/gs0NeyJaPFQwcd63kwj/TgwR1tcZVgwRHos25dt+u1FN8b7PsTki01ZJYNOw+x8JRZMkxT0vMw1pyHWFSr48SG7GZ3HuKploXYOQ/NMMpFUcXMEu8MVNLapnYeomg3/T7tJy/wnDdwDjwPfoniwc/pPPR8CWbGYkblHHoe5iRtSXJ9xYPtPBhG32TJcPEgrGzJJP2g8+AYli051vNgHJZ9+BCVN+HS6LgCPUn6wGMfb5LI5L2+wDCtPIxj/s10B7Upz8PAnIfZWToq2dKg52E02VJvULbkUuxvpo6f9nfrVNigtp6Hhhg1qrVs63toN6L0iQ0vcuIaybRBbCptKeeYXdV5kIsVPA+JAy640Y5DVudBv8jmpHYIzR21yJbggGAXpMaoS7Zk05aM4tXSeXDRsZ4H45DvwTeU8N5xCH3Z1s5Dhmwpc0icgQV3Q7Kl5JwHI8lRU4QjaGD9UiQJz2So8zA8JyutgBwtban5e8/sXAEl8AviTdOoEtUar14rtculpxYksd3suK4wjGpNZBHntY5JFw/bysmW0g4VjU6XYTGUfAMMk6DmRLZUW4IPAEnCdh5MEqaY1eN5mPRNfFbxPPV3dAwWD8LpqqhW23kwCsk+PDJVPMQ7D+16LcVv76FhmpxMiWTfxG59KFmZdOdBPUdahdD3eaY6D0QYmjBtQrbUcQQkq+NFUa0pnQe3gmE6jOtt/vUyO1dACbhA6pNG11GtpzJzDOIL6MqypcROdry6jxbo0deLLnC3u4A+O5AlDdNphUjHiXYcoso5w/MwJ60HbcKtQ7bE5MCZgjeFmSHsPNTjeSCWcyPXqxPPD2RLrsHiwVWyJWuYNgtJD76h11PXFei11vOQ7Dz0MiVL6jEGEopC2VJTnodoE3GmOg9EA+u7Ikl4JgnZUrxjk7V+AgLvT2nZ0vT47WbnCiiBXyT1SUEvoL0SiwQ/Gd9WlpTiIW6wCj0PA2lL+f6NrkPYioVSxYOfYSSPax2zhpyESVBz0nmobWoxlGxJWNmSOfRNtqa0JQdsNfUG0LIl054HJVuyryejyL4x2VLXEejpp6dlmyZDG4WJmM44zGwmoYhIvZdNeOE4sA7w09cBbUZQYsL0COtEMA8PiQv+boteVDykdx7KJ3paw3RDFEl90kjq/fKIr5+ryZb8lM4DR4bpFGmQXzCzouMIbMECuITngRmpGr9uLKItHHIylLYUHWMuCDsPNQyJs4Zpo+g5D+bTloKiHtJq6g0Qdh4MPk+O24Eghtdv/iY7S5D0IQ3KlmbH89DL8TsEu/UmFtwkGpgwHdtBz5lX0FZEwvMwyjpRXb+c8DxEsu9ehuxbf856HqacUaJaQ+lOiSnT8eq17FRqdWLe0AJncEhcimG64ALvOAJbeKH0hOm0Q8Uj2rIq57lLWwoN07Z4mHbCVnRNsiUHstomgSUVPefBtGwJAPpe39gxLQBxH76x4oFinod23T8GPA8eA7KfKVvK23WuDDmTn/OQtg6YIdmSICTSllA9TSwlqjcu++4VDYmzaUvTjczYYc9Dv0gWS7S/pUnZUtzzEBYPsW+R+Rd41xXYgiWlh8SlafzKeB5ozuY8UK1RrS4cK1syBsmaZUtkiwcT+EHnwTUoBXSCm7jf7xk7pgUQ0gOb9Dy0VLbEQ52HbNlSnt69MsJpQLYUGKYHZEuzs3RUaUvJAbwVD5IyYTzs2Hicew1Um/Ngh8Q1wiieh6j1NFnDdNzzoGsEfyhtKfuQ3UC2VKbzIDPM1wNvGhlpAfOXtqT+DiYlFhpJDgTsYtQYtcmWCAxSsiXreRibejoP6ibu2eLBKII9g50HgcWWypaGZjrlGKbzknYqQ87EZUtqGrjS5eftoLcVIkJ8eTdS2lJKVG/oFfHVsEpBSFWLdCskelrPQ0Nk7bDnEVWPxU9uPEGtuudhcNdiYM5DOGE66XnIly1t5QVQmeKBMy7qAc+D1uwlDdPBMeZlDcXaMG2+eLBpS4ZhhgRhtIk/BYcmx8qWDKE7DyajWt1O0HmwsiWjCPbAhmbcdB2Bnn75tOx9b3CmU0HxkDNduDJi8oZpIJhZ4M1q2hISaUvV14l5sqWex7mD9ToOlZe5285DM2TtsOcRl+4U4SdbmaVPLM3zwOi4esK09hWorzFzYdpSxyFsQbniIct8HXoegrSAjkNDUql5S1vSnYfaDNNWtmQMYl8VDzXAJILOw3xc93XiB50Hk68p4djioQ4Ee0YN04t+sASZgsVQFYYkyn5/SD2gCWckjTthGmjEMA0o+XZcvjxLsqXhtCVUT1tKlS3FDdMys3isZJgm23lohKwd9jzicVtFcMzEXL14SKQteRLdYHc73N0P3rDCidCFnocFCK+4eOCMLkYnMWE67eLX31dmDsZMELxx19N5cG3nwSCqeKjpLc52Hozh++blZRQUD9K3siWTOCY7D26bOw/xe/1wTGecUO9u4p7RgGEa0MNyeTajWhOeh5HSlkLZUjxtST3fuujK6tYo7481TE81ap5Bte/pVuk8SMYSt3yxEX3j8K7Foi/DnQoiAlG8eFAf84p/LVtySqct5cx58H2VU51y8UdpS4U/ZibQE6br8jxYw7Q5mGVtxQOTgGOjWo2go1qNpmKFhmnbeTCJYB9SpBuDq9JxBBb1Gqhlutf4vT6a81DkeTCw4G7AMA0EEjNvNj0PKm0p+v8iSXgqMs3zEHlG+172VG79ty13sla21AjKRT/qnIcyhmlgoaOrzSpRrYNzHtQI+MGdfodoqHgok7bk+FtLnXeWkQdQmr24ByNOsisy8+g5D6YTfKB19M2/KcwKgiW4rrc4ocztpSeDWjKRungwWZAH76fSt8WDSQQPzyQala5LWAw7D+16HfHAvT4/bSncrTfhE2io89BNyJZmyvMw1HnIV3WkkiJb6iTmZGXJ1qrNeRAAyHYeJs0oLvr4dMUiJEe7EeN4HnypPA3xxbrS5QUPDz4WzXnYigU4/rbCXR0p0zsyA5o9j9NlS3OWtgT24TPBqWHnhYWSwrQt83xqmYBsyXYexsf3dKRuDcWDZ2VLJnHYAxv1PAT/0zLZUrzzUGSYNjpYTTiNdGk6Ds225yFePIwyYTolbSk+JytvwnjHEZBcYVaWcG3xMGkko7KLvuOU9zBIZiyJ70aUPrFBz0NaooEQka9AL9TzfpWuGwyJAwrjWrM0fsk5D2m7DWkD7GaaQApT+c2lBKERcQpakjMBM2QNSUsAAKE9D3Ny3ddI1HkweDvSngev+ZvsLOHCAwylYnUdgUXZXsO0vteHhulMz4PBhCKiZgzTwe64DoiYteJh7AnTeXMegsncWcVjt+qGs3CnotienSugAD1BsOo1Een+y3kedCtznDkPabnQ8UQAPyweitOWABQWD35Gmy7edVFRY8OP0X/PedmAZamKh8oTKMsce4qSFGYBZZg2701RB3fsnAdDhIbpOjoPVrZkFAc+2JTnwY15HqZgMVQFyRxFmYdzHtKLql5wfbd1wjSg/SlRp7VrIjlqShiaMC15jAnTMdlSbP2UZ5jW66rSPtmGfC9Dp9H0CUyK0GRc8aJYqFAVSo4eX23C9KCONMqFjs7ViVXHeuMhN20pkC2pA+ZPmZZZUa3uYOch3fMwX50HYgkJqr4zUQKeoiSFWYBqNExDCJu2ZIg6PQ9so1qN4vJwMuCodByBbXoNNAWLoSpIBlyH4AoqnvMQ7ta32DCtPQ+hBKumTZkGGJ4wXX2dmD4kLjBMa8+Dsc6DMxVrhLkpHsLd+hGjWkt5HiRjSScaSV6ahOchTVcYT1vyS8qWNvOS4IAFsqXCtKVszV7oeSir12s5HBQPdciWbOfBLMQSXNOcB5ADQdbzYAIp60tbktIWDyZx4Wcag6uy4Ar4egnSMsO0L1X4ipLzsHrPLoxqbW/noRv8nuHaZIY6D5SY8+AzV1dQpsmW4rJvjzOLxyqzxADMn+eBiL5IROuI6LrY5/6aiO4homuC/14U+9r7iegWIrqJiF4w7s/XhWVlw3SlzoOK43L0bkRZhjwPw4kG8eo4imotNkwDAHqjeR66JTwPTth5yP0RMwOxDx+iehpDCaLioV27cNMKwYesIRULUAPNBNjKlgwQGqbr6DxY2ZIxmFmlwRkqHjoORUMcW/aeJ1lJWzoOxWRL6X8XowlFDXUeZtkw7RANZJTIUaJa8zwPgdyr66a/v0XDeK1hOoszAZyQ8vl/ZuZDgv++BwBEdCCA1wF4SvA9nyEab1vKH9nzoFtPxU+s9g50HKooW6rmedC7/Hm6PFdQzDCdL1vyZfqx4jnFvcwhccEx5kS2BKl2s2spHqxsySiq81BTe13YIXGm4Do6D4Eu38qWzNH3JLrkgwzOeZAt7TzoDbeu6wSG6TzZksEFN4lG0vg6wSyCRZO/y5QgBFLSlkaULcXWcXG/rIrez+g8hFL3kkXhvBUPzHwZgI0lH/5yAOcy8yIz3w7gFgDPGufnl9mtT2NBTwksOWFaUPRCK39y6Z6HgeJBRJ4H/THvdyEi9MXS4ID5nQc1GXv4866jUoXUjkN6203LluZpwrQPUY/ngWzxYBSW4JrSlkjPebDFw9hIvZNqNG1Jv5Zs8WCKflCIkaG0pY4Tly21rPMg1cZZ1yG1NshNWzJdPDTjeej5UbrcwgzNeRA0POfBRNpSJEfiIHAma0ic3qQt23mwhmnNaUR0bSBr2in43O4A7o49Zm3wuZHR0chVXfRa21c2bckRFOgDR5/zkPYCjScClPE8AIDnBsVDYdpSdqWtxtIXR7WWzihuO8HsgFo8D8J6HkxSr2HaRrWagmtMW2LfvpZM0e8tAgDIkGypG/c8TMFiqAr6ntkJjMTwe5lG8p7JqNYGJ0zPqmxJEKWkLVU8SGrxEJswnZO2NFJU6xS8Xpq+Aj4LYF8AhwC4D8Angs+nPXWpd2kiOoWIriCiK9avX5/5g6K0pWonGFaPpYbEqeJEJxOUJsPzEH+BDkyYDiVY+b9MXwSG6cK0pexjdR2BvpdtmJ43zwMCE24dUa2wsiWjECSkyQVp/NhB8VA6Xs+SSWiYNup5CBa4tngwRr+nFkjGiocB2VLzi6EqsC4eHIGe5+cPiZsBw3QnWAf0fQlBI+zMTzGOGJzzwMwjpC0F7zOx1wYRxYouzh0SB1QoHsimLYGZH2Bmn5klgDMQSZPWAtgz9tA9ANybcYzTmflQZj509erVmT9r1LQlV1QYEhdLYDAz5yE6V4pNQYyGxOX/Lp6jZUsFxUPORMWOK9Dz/UzPg/ajzkvakpYt1YI1TBuF2K8tbYnIgUtsZUsGkHV0HvRN3MqWjNHvq86DcM15HqLOQ7teR3GVgacN/4Weh/ZGtXZc5ePMk9+0FSIMpy0ZMEwDCA31izl/tyqJngDmz/OQBhHtFvvfVwLQSUzfBvA6Ilogon0A7A/gl+P8rLIL7pRzDPR+xYtjGUR8qWSCKlGtGZ6HRNoSV/A8AIDnLFP/KDBM501U7MZ2HPI7D/NRPNQZ/2kN02YRLKMEK+MHd+CSLNWRtOTDssa0JftaMobX156H9EVyVToOtdfzwGrR2XEF2FNFVV7aEpnarSfRiLm86zix1KDZKh5U2tKg56HqJnNm8eBGcq9Mw3SFQcQApka2ZMb5VAIiOgfA0QBWEdFaAB8GcDQRHQIlSboDwB8DADNfT0TnA/gNAA/AnzKP9+6iNzZGScnpluwk+PFW5jieB2+4zSli1bEfpi3lH1a4XfiLAk6BYTpvomLHpbDtlut5mJPiATXq6O2cB9NwfZ4HcuBS33YeTKBvhCZjdYPigWznwRiepxZIwqDnAS2OalWdBwJnLBw1PV917Y1IXclppHjQnYe+n65AaDMipuoA8pUYmaQMiQOCtWMwHyOr6IoGEVcxTDe/RphY8cDMJ6Z8+gs5j/8YgI+Z+vlR2lL179UZx0Vw4B1YGNvzMGywErE5D1wyOarjOuiJpVhaYJjmnHSB0DCd0XbTASnzUjtow3QdkO08GEWwX1xhj3xwBy4t2iFxBpDSV2tIk52HULZkX0um0J4HU7IlvQhlckAtjGrVG4Wyp4uHjM6Dx+YW3EIAQRE3SULtvpet3W8rIuF5yFNiZOL3lM8qcb/pxIzmxjwPVrY0WfwSsxGyKGuA1jrIsT0PgQY4OedheMJ0UfFAWKQlhZ6HvImKuuuy6MvUqZLzl7bEtcmWZFg8tGsXblpRaUs1yZYCz0PpeD1LJvXMedCdh+ZvsrNC2HlwDUW1ulHx0DbZki/Vva/rxhbzGcVDz/cHJMhj0eCEacnA1r4/c7KleJIloNYyI3keUjpPXVdg0SsyTEepTOVO2J2K18tsXQU56J3xyi56oLQMSU2djKrN0iQ8D3rSYNxg5RCF0quyEqyOI9BDJ9Lj5Zx3ZtqSK3LblfPoeahzajGAqdhVmAUIElzTc2WHxJmBmaNiuQbPgy0ezOH31X3EcU15HnTxIFq3YRKf6RROMc9KW/LSZySNRGOGafVcbV70zP0uU4IjBuc8aAVJJfx+avHYcQhbFtV7UFbRVd3zYOc8TJQoban695b1PIRpSyUN1tE3Dnoe9EUUv9iIkJK2VHzePorfmPMmKnYcgW19H8zpUXP62+Ynbak+2ZI1TJtFsATX5nkQyjBti4ex8CVDQA/hMS9bIvbmZ4BlzfiBYVoYKh668eKhZbKleNpSkechT+9emYb+VnqBu7nnzZ5siSglbaniQXI6D5t7QfGQ8XdbqDznYTo8D7N1FeQwatoSUL6ToOclqISi8ec8xC82lbY0WDwU6fLCITwFLa68iYodh7B5MZBRpbwBEpFq+83J/bnOtCWbEGOW+jsPXE2eaBmi58uoeKhhzoPDPrx5eXOqGS9IFTLVeegGMlim6dhJrULkeaBY0k6WbMlgvGljsiX1XG1enEXZEg14NkfzPKRPGO84Ilo/FaQtlV4zWs/DZOExigfleSi+ASnvAKEbJBOUJnPOw6DnIZm2VEa2pDoP+ReazKm0u66DzUHbLesNMDnefaapc2ox2am4JqlzSBzIgUPSGqbHpO8xnLDzYDJtST3vHfJtd8gQuvPgGJzzAEC9n06BhrsKHMR5dl0RS9rJnvNgzjDtNDIToxuTLc1e2hISaUsjeGP9HuAMe4FU8RCsn7JkS+4oUa3NrxFm6yrIQT8vo2Qt60EfRcR1kKVvWMzqjbNgwnQ8EUB/LMoi7jgEn0Xhm02eQajrUKztlv4YIWhuolrr3M0mRy14pG/jJU0gWNaXtkTCeh4MUFvngQiSXLjwQg+ZZTxksMPudkx7HtrXefBj93qSBWlLRjsPzRRasyxbSnoeVOeh4kGyZEtOJFsqMkyXj2q1xcNEKesTSKOsYTqugyzdgtJvmk48bWnYMK2kQRU9D65TSraUZxDqOAJbgrZbVrtS0DxFtdY458HKlowiIMF1pS0JBw5xtWGQliH6vox1Hsw+V5JcOLDdIVP4nnpfMidbCooHUOs8D5IDf6MT6zyIrOIhfUbSSDRlmA4WvlsWDSZHTQlEw1Gtoxmm0z0Pev20kPF3052c8mlL01Fsz9ZVkENZqU8aZaNateehkmFaDzFKdB6SQ2WcmDRIm5OLkqM6DqHPxbIlP0fj1ylROTsJw9EsQ3WacINrQHq2eDABsQTX3Hmwnofx6HkSDnQr1WzxwMJBB74tHgzhezptybBsqaHd9HHQ0pauK0AlhsQZSyiaAsN0lgKhrTgiWlMxc7iOq4TMTlsqWj9R4J2pNueh+dfL3BQPemd81AnTpYqHQP6j0plKPrl6YZ/wPCTfbEQsqlVLhIp0eaXTloKI2dRjuCKsyq3noeYFabB4sp0HMwjIaGq38YPbqFYT9OOyJcPPFYeyJfscmYCD4qHTNZu2JNGMjn8ctLSl64goDjjH89B2w7TeNZecrUBoK/H1y8jrxAzZUscpXj/pr5XeiKLpSFua2ITpptEL7tE8DyWjWgMdpCOovJwhpXjo+3KoNShE9DuEMysKPQ8CHlNx2pLM7zyk/Xvw3GhuolqJpSrI6ji2li1Zz4MRiKVZE+7AwR0IK4kZm15ctmS48yBFB64t8IzhB0EOjjHPQzAjqIWGae0T7DgCDmvDdLbnoe2G6TLrgLYiAtkSM8fWiRUPkiVbGvi7Za/XKvlkredhsshwt77693YqpC05QQJD6QshHJA0LFuKo+LEkmlL+YfuugIeF+vjLhhQYAAAIABJREFU8tp08RZllmZvnqJagfplS+y360Y6rQiwHRI35fR9hkM1pC0BgHDgWtmSMcLOgyHPg+sI5Zdr4ZA4GaQtdVxCB9q3OIk5D810HuIL31ksHgC1KStLqjqG8HupxWP8ec+7BrpVpO5WtjRZQp9AjWlLkrV+TcCTXG43Puw8xIbEecOjzB0R+QpCw3TZzkPBhZaXtlRmx8GZp7Ql5vomTAdvPixt58EEAn59siXdebCSmLHoeTKQlwnjyVgsOnDJs8+RIXQKnKm0JSAWJ96yzoNWGXQdgQ60bCnbMG1swS2aKbTiSohZKx70r+Mzh02d6nMesmVLmrzuU1lpPAA7JG7SyDE8DwtlDdNS6SArjRtP8zyk7FTEEwHKDrzrBoZpLkxbypvzUNx2o1hXZNYh9mvsPASeBzvnwQii9iFx0qYtjYlOW6qlyBNuIFuyz5EJ2DNfPHQdoWRLU7CTWgWdttR1BTqUXzyY9Tw0Y5iOL3yzFAhtRXcZJPPoqZx+lmG6XNFVdoNanZyVLU2UcdKWyka16ogv/UIrVUmmeR5Shso48ahWXR0XFQ/BhOmixWhR2lL8eGnMVdoS6jNMk2OHxJmEwDV6HgQEpDXjjkk456GO50kEhmkrWzKClPna/lHougKyhVGtvuRQZdBFgWF6BmRLZTYR24pe+0gZ+UpNGaaryJYqeR6moFM3N8UDj1pRIjCzFCwS4hFf+iIpteOV4XnouClpS9rzUNK/EU2YLvY8ZGn8uiXalfPkeVBRrXUl+Ng5DyYRXG/akmCrpx+Xvldv58FGtRrEG97oGpeO7jy0rHhgVovOjiPglvE8mFpwNzznIfnvWUCvCSVzeBkaKx5KekWqGabtnIeJ4pf0CaShntj81XE84qszUuch5nlImUhJROGUbOZy/g39xsxFxYPMli3Fdxkyh8TNWdpSbZ2HMKq1+TeGWYDqNLfH0pbmRbJXB2HakuGkJQCA07GzOAzCepKyyeLBJfjcPtmSL/WEaSr2PBiPam0ibWn2DdN+LG1pJNlSyuuirOdBqVvKGqat52GijON5UE74/EVC/KLTL7RSN63MOQ9JwzRiaUvBtxQNiXMFPDiFO9kyR7bULbHjMFdzHsATSFtq/o1hFlCL0vo8DwQJZsyNZK8OwjkPtXUerGzJGH7+InkUWm2YFoQFt5xsydhU5oZ2ncvKb9pImLYkI2m4McN0XLnhZh+z0mww63mYLLJkvGkauvWU132IJyDpF9eohum+L4dMSYKG05aKNgAWSnYectOWSrxpqLSl/HOZFYj92ky4ZGVLRqlNSw8A5ICC16E15I5O3+PaijxyOnDh2+LBFHr+jDDoeSgprZ02tL+xE09bSvm7MDP6Ppub80DN+EO6JXfQ24heE6q0pVGjWovnPOSmLZUcBwDAFg+TZuSKEiglQ4rLlsY2TKdEuwkR7e6XzSLuuFTqjZlz5jwMah2z0pYwX52HmhakIjBMT8MbwyygnqsaPQ+B1tlq6kcnlC3V8DyR04FDEn1vPt6b6oZrMky3s/OggkI6jkpbYnJSC2C9IGy7YbrMOqCthIbpwLca/1xpstKWBjoP+WlL1QzTsvGp7HNTPIybtgTkFwO+jLoB4ePL3LRCw3R08+z7cugFqqcgArFCqKh4cAQ8iMLFqJ8X1VqicnZofjwPguvT0ZMQ8JmsbMkQTq2dB6EmWKOkPNGSip7zQDV4HshRsqVFW9yZwfdUMpLB56rjqPe8tnUeIs+D6jzIjG6MXjMYW3BPg2F6xmRLYVSrHMfzUGyYLvQ8lI5qDV5/DRfcs3UV5DCu5wHI32GMz17ohI8v8eSW9TzEdvdLex4cAcklDNN5nodSaUvz43lAjbMDHEHwMB1mqLbDzPVp6QHleQjevK0sZnT6NRqmQ9mSLe6MQNKDbzhpruMQfFDUum8BnJAod+CDM4oHvSA0a5hudsL0rMmWos5DXN5eYZ0offWcFAyJy01bcsuNAwAQ3dMaLrhn6yrIIfIkVP9e/WLJqwxlbEEfPb7KhOn8IXFpnoei36VsS1jKbAlUmTkPQkRJULOOYGl8Em54bCL4JQzulmJ8yfUOiSNHXQuwxcM49H0JQRJUw/NEbicYEmefHyPUUDx0XUelLbVIthRXMXRLdh6MyZZ0kT1hyQrF1jWzZ5hWH/2BIXEV7vF+tpxP/60cQblSqIVKUa3TIW+erasgh7JSnzS0S76UYZqAbvj40Q3TyepeCAo3Z8pWx8qM5oBKpS2lfy2+4+BmXPyCMDdxlSr+s57dbEGkZGZWtjQ2kpVsiWpOWwLYLk7HoOdzbZ0HITp2SJxBSPbhk7mYVkDJOryWGabjuviOS7nFQ8833XkIjtNgXOusRrVKOaLnwQ8ijHM6D0WyNTVLrIJhGrDFw6TwR3XRo6TnIWbIrjbnIW1IXIphmhDrPCD8WUXn7ZcYwONzdtpSuNvgiMy/nUpbmpfioUbDNEHt7LXoRjqtSGaIOg3TwXEFGItWFjMyPU+iQwyqwzDtKtmS9aSYgaRnvHgIPQ8t6jxEgSUIDdM+ZXUeAsO08eKhAemSqxfCs7VsDIsH5tg6scIBws5DdtpS0d+s41Y0TAONrxNm6yrIgUepKANKyZZiCUidEo+PvjFlSFzqnIdRJkwXpy0xc27aUtctrpwpZuaedUSNUa3K81BscLcUI2v3PATtaEgb1ToGfV/CpZo8D6KDDsnyw5csuRD3IWsoHryWDYmLqxi6jprzkPV3Me55EM3p3WdVthT3PJQdwDtA2HlISVuKbb7mMZJhel46D0T0RSJaR0TXxT73j0R0IxFdS0TfJKIdg8+vIaKtRHRN8N/nxv35/hhzHjplDNPBlxwDcx7SPA8UMyVzSQmW9jwQZ19kRUbyTok3DIcwN2lLBEZdLxvreTCHL7nmtCXdebCa+nFQxQPXOCTOznkwhZAefMPPU9cV8FrWeRjwPASG6ayOjHHPAzWXtFNWgtM29NLHH0hbMiNb0s970fPfrWKYnkPZ0pkATkh87iIABzHzwQB+C+D9sa/dysyHBP+dOu4PH8kIExDObSjReRAUe3yZHa9E8aCGysiBiC8giEMNDlc2dlYP4KEc2VLRwLlOibbbPKUtEdcoW7JpS8aQHAyJq2FHG0B4XAfSpvmMQVg81PE8OS5csp4HUwjO3mEflajz0J7nKNxwCyTKLrJlS5HnwWBUK9DolOlZTVti5oHgm9LkGKbL+kS6oxim5yWqlZkvA7Ax8bkfMYfb4pcD2KOunx+fAF2VToliIL6gH8fz4EslIyrjeSj6XTrBhOm8i6zIC6LN37nFg4iSoGYdgfpkS4Kgkkds8TA2UirPQ92dBwfSzhEYg0VPwqGanifRQcd6HoxB0jdePHQdgsdofCFUBRlTMXQcQhcevKzOQ3Dtmfc8WMO0KXShMJi2VOEAJWRLZQzTklFuHTVvsqUSvBnA92P/vw8RXU1EPyWio8Y9eGgyHmvOQ553QH1UxYP6GaN4HsKdimRUa3zCdEkJVscV8OCAcj0P6mPmnAdHnVde2020K6Z7LKjGBalDtvNgCsmstPR1FQ8iJluyi9OR6ftcX+dBuHAg7QRwQwj2wKKmzkMDi+FRkTFdvJYteUWdB+Oypcn/vcpKcNpGlLY0+NyWpoRsqdAwXcUnOyWGabPvBCNCRB8A4AH4avCp+wDsxcwbiOgZAP6DiJ7CzI+mfO8pAE4BgL322ivzZ4zleQiLgZzOQ+INBRgtqlXHdQ1FtcamOJe9wLtB50FAqtV9SuFUNFFRx9Tm7Zw4okJSQMupc3YAUbHB3VIOP2Vyu1FinQdrmB6dvhcYpuvwPDhuENVqnx8T1CFbCj0PLXrPiwJLCB2h0pYyOw++4c6Djp5ucMr07HUe1Md42lLlIXHAgG9Vo5/3hRKeB0AVm0uLouBt50FBRG8E8BIAJ3HgBGbmRWbeEPz7SgC3Anhi2vcz8+nMfCgzH7p69erMn8NjyJa6JWRIyfg2oKRhWuvlggsva6dCpS0F31LSv9F1hJLBAJk7FUVekPANw83+WfPkeVBD4upLW/Lh5BrcLeXgQLxax/AxAANpS6UmyVtS6dWYtgSho1rt82OCujoPfRbgFsmWOKZiEIKUYZrTr1+94Wh0wjTQqGF6Vj0Pkrm0JHyAlNAbTdl4W+1xLbUJO4eG6SGI6AQAfwngZcy8Jfb51RQEfxPREwDsD+C2cX7WSBVlQBkPg+4KDMx5qDRhujPwM5KGaaKoaIhLpHLP2w2iP+M/J+O8C4uHIsP0nHge6pQtCYIdEmcI3wv+hrXPeZDlh/tYhuj7Eg7qS1ty4VtZmSGcGoqHrhv48trUeUioGDrkw8u4fqO0pRkwTJfYSGwjoedBjuh5yCseSvpEKvlkp6R4mJhsiYjOAXA0gFVEtBbAh6HSlRYAXBQYdi8PkpWeC+D/EpEHwAdwKjNvTD1wSYx4HnLTltRHQRSOIi+1I5mQV+ifkdQVOkRh96SsBEvLlgZ+TsZ5Z0mgFkokLAiKjjPrKNlSTROmg85Dm8yD0wqnzE8xCsU7D3ZxOio9r8bOQ2Bg9G0xPjbMDAc+mJYYPa7ujrP00ZYlabJb75LM6TzozUBD13eDhulZTVsSYechtglcSbaUXTwslPCMxr9uPQ8pMPOJKZ/+QsZjLwBwgcmfH8qKRrjuS02YTuzgq+it6lGt/TDabdjz4Ff0PDiCIAsmUhYVIqXmPMxV2pKsOH6ywrEDwzRZw/TYSP3aq9swTXbOwziozkNNUkCdYOf1zB97zuj7jA48sGNatkTw0S7PQxjnGdw0XUgsZog4wvu5qd36RmVLwS76zBmm1UfJPOBnKU2ubKmGzgPlbwhPitm6CnKIT4WsSjhhOqcYSLa7Og5VTFtKeB6SxUPM8yAL4lU1RASm/BZXkRfEERRE0mVfKjRHngcC19Z5cKxh2hgyuN5J1PQWFzNM2yjQ0enp4qGmtCUA8L2++WPPGdHzlJ4qNCodV4AL4sSnjeS93iUf/QyTa9Zm4MiEsqUmolpns/Og14QyiMkHKqYt5Rimo83X4qhWID+UJ2RKZEuzdRXkoAu6kTwPbrGZJdkN6Lolh34MdR6y0paCh0tl6il7cVPBm00Z83XHEbk5xc4cFQ+ixqnFRIDH1jBtApmzG2SE+JA423kYmb7HwZyH+mRL7NviYVz6nkQHvvHXUycYZMotimr1E/d6F1LFzaagNxzNGabzlQR10i3hf2wjehPWH0hbqnCAHImsK0oOiSuxxgyxxcNkiYbEVf/esPNQ0vOgv6dc52Gwas3zPKifo1prZS/usHjIeLMp4wXpugJdN/vmLsQ8eR5qnPMgVOfBypbGR6ct1TckTh1XQOZ2JC359CfQeWDbeRibvi/hwjNePCy4Iui2tqd44IS0xYUfBZMk0PfzoqjO0jQ8YVr7OWeJaML0iMOEczaqiFR0f1G3RntiSvnnpqR4mIo5D5OgKFUoD0cQiIBf3/0wzv/V3eHnOy7hhKfshqVdJ6pYdaXpCtyyftPA4+Psu8tyPGPvnYMLgHDnQ1vxi9s24pb1m9T3p8iWgGgKYunfQzjKcl6QtpR3uG5B52Ge0pbq7Dxoz0PTbwqzgAzCCqiutKXgJr5ElNwtsqQSymFqSlsCALaG6bHp+RIu/NQpuuPQ0aEeLZIt6Ze73nBzINFPGKavvPMh3LpuE66+6yEAdXQempEtFU1KbiO6ThhMWxqleEh/D+s6otAnov+uF/3mAdy+fnPuYw/kzTgIaFzePD/FwxhpS0SE3bZfgktuXIdLblw3+MXXAq982h6RdyA4/K7bL8Evbt+Iq+96OPWYOy/v4qoPHqcuPOHio9+9ARf95oHwGKu3Wxh4vL6YOUgEKF88uEHxkNV5KDZf77nzMuy507LsHzFHsqXazJ0AHIFgzsNiLcefJzi43qmuFnuw2F1w2HoexqDvSwiSo7WEi9BpS7bzMDbKMO2DTXseHNE6n1fS8+DAV4PuYpxy1hXYsFkZ9VetWDC3W9+gYXqvgnVAW4nSljhsgFVLW8r2PADF6ycA2GX7JSACTr+seCLB0zt34kIHjW8yzk3xELnoR/v+i//8d/HQlugmtGHTIl72qZ9ha09dbX4i4uusP3oWHtyUnvLxqUtvwX9cfY/6n6B42Nb3cdDu2+PzJx+KZR0HOy0fHHU+WB1X8DyUTlvKPt4Ff3JEboyeIyj8+840es5GTbvZRGouh/U8jI+vY5Jr7jy4gucmaawOfMkQTl2dB7XQFWyLh3HxpcQS8tE3nLbkCoKEALWq8zCoMnBShsRt7fs48Vl74rRj9seOSw0WXA3Klt5y1D5485H7TPzn1o1ISMKBaJ3Y7/exdu1abNu2LfsAvA/wgvOBB7YB628Y+vInjlsFoh5uuGH4a3G+84Z9ULQNtWmbh8XF1biBzgd6q4CCY5ZlyZIl2GOPPdDplL9W56Z44MAnUCmCK8ayrotl3ejPtSRoQ/lBqarXD/r4C66D3XdcmnqsHZd1ogWHVCY0z2cs67iZ3xOfguhLLl0EcUEmcJmJikWFClGrJKujo/+GdXUeKJgw3aJduKlF1ixbCo7btcXDWHi6eKhlzkPw3teihem04kmGCw99w50H5fOiRmQ4o5Ic0upADnkePMnYYWk3834+MmHnYfJ/LyLCDKqWYmlLkZ9Fr3nWrl2L7bbbDmvWrMleO27ZADzsALs8EXAX0h9jiAce3YZHHn0MTxQdYKc1wNKdxj4mM2PDhg1Yu3Yt9tmnfHE4N4Zpv4rUpwSu0Lm81WYvqO8l9PVqW3qAcOBJmfu9lLjAS7dBKX+nYqSJignmJm0peMOuK/5TBJ0H2M7D2Ei9YKxLthQsdjvE8Oaicq4Hz2cIrtfzQDZtaWy8QLZk2vPQys5DeK9X/y/go59IW/J8GSbtGEXfe+wGkzH0slClLal/67Xitm3bsHLlyvxNZw53jms8y+hHhCstQ2suIsLKlSvzuyspzE3xILmig74Ax4lGmqvjl1+EO4JC74KWLXmS4ebGoSL8OX5VwzSQk7Y0+vyL8EfMTfGg/oZcl2Faex7sjWFsuPbOQxBbKBieTVsaGU9KCPg1pS2pha6VAY6PJzlIxTIrVnDC4qE9BXg4cFZ3HlgOFA9V49Qr0aBhelaJ0pY4tgkcfb1YraLf/ydQPADgGn7OKIqcOSoeyseblkHvKnhB8ZDUQeahkxe8WPHgS87dqRhMW6qQBhBqJNNvoPq8R5Vz6XObi8AZ3XmoM22JHQi72Bkb6ecnYIyN0LIlaWVLY+BLDhLM6pvzYKOPx8eXEh14INOdB0fA1wvvlnTwZMLf6MBXKXkBujNRSzJRg4bpWUWvpXw5XBiWInz7r6d4cBwHhxxyCA466CD80R+chK1btyR/cGl+8pOf4CUveYmR85qf4kHyWLvrSfRCX3sekjrIPBwR61rEPA9OjhwmbupRaUslT7TAYDXSRMWhc4u0gjON3u2pa8K0nvNgbwxjw2ExX6/nwaVoA8FSHU8GsqU6pIDBc2+Lh/HxfIYLH1SDYdpHfqjHtDEw00lKCAx2HsLwlBqvaStbMofuMsh456HSWlHLlsyel2bp0qW45pprcN1116Hb7eDcs78c/NggwIUZsoHCe26Kh0pSnxI4GZ2HMhdd1LWQoeehsPMQ8zzICp4HonzT4EgTFRPMTdpS8IbNNXkeiADPypaMEHUeavY8WMP0yEjJYEZ9nYcwbckWD+Pi+xIuyfBvagotWwLQmgVxpDJAeF+NT5jWa4JaPA+282Acim3MJj0P5ZicbOmwI47EnXfcjjvuvhdPfvoReNvb3oanP/3puPvuu/GjH/0Ihx9+OJ7+9Kfj1a9+NTZtUjPDfvCDH+CAAw7AkUceiQsvvNDYucxR2pJZzwORmrSY9DyUueYGOw+B56EvQx9F+vcg/Dm+HEW2VGCYHqvzMB9D4pglCPXJllTako1qNQJPJm3JGqZHRy+yiGvyPGjZEvtg5rGkmfOO76nYcXJNy5aCtCWgNQviaKYThXLggc6DXz48pTLh/dy+55jCias6OFYYJvjIf16P39z76PAX/J76r/vLyj/7wMdvjw+/9CmlHut5Hi656Id45hHPBQDcdPMt+NKXz8JnPvMZPPjgg/joRz+Kiy++GMuXL8fHP/5xfPKTn8R73/tevPWtb8Wll16K/fbbD6997Wsrn2MWc1M8mPY8AOrNwUsUD2XTloBqngeiqOBg5tIbquQUFQ/q4zhdGUFkyvg/1fiep14wNS1I9YRp0ZKb6DTDwc01vP5No+c8kPU8jEq4g1vzhGkXnnp/ncWcyQkhg8QqcroFj6zGgGypJZ2HcOCsiBUPiHce1HtPLdebNUwbZ8DzUGLu1aTZunUrDjnkEADAMw87Aq963cnA+iux91574LDDDgMAXH755fjNb36D5zznOQCAXq+Hww8/HDfeeCP22Wcf7L///gCAN7zhDTj99NONnNfcFA++rBBvWhJXEDx/cM5DOc+DnhExmLaUd366OmauKMEqaHOaSVvCXMiWQl1hXVGtIpjzYIuHsZGTSlsiDuOaLdXQcdXENc15CIqHDvwgzc78j5gX/H7QeTBsmHaEALfM8+BzTOqriweZ5nmos3hox9+qDYgBz4P6d9pzl9khePQ+YNP9wG6H1BLXqj0PAPDQlh7u2bgZALB8WTS1mplx3HHH4Zxzzhn43muuuaa2juvceB4kj5colEa881DFO6A7DH1fBoZpRxnSctOW1EedtlR6sR8OiUuXwkhDnod5iGqNFqR1pS0BHoTtPJgguN6p5rQl16YtjYyWdxD79QxeDBa6DqQ1tY+J9hDVa5hux3MkB2RL6r06Llvq1+l5sIZp40R+0uEJ0+WY4JyHjM8fdthh+NnPfoZbbrkFALBlyxb89re/xQEHHIDbb78dt956KwAMFRfjMD/Fg+G0JSB440vOeSjxhpHqeZDV0pZK1w4FE6Z9A54HIpoLCSbrAqzWtKUgqrUlN9JpRXeJ6hroF3keYD0PI+LFZUu1dh68sFCxjIb0VedBGI9qbaFsKS5tyfU81PDeYw3TxtHrMcmxCdOVDdOTkTllzXlYvXo1zjzzTJx44ok4+OCDcdhhh+HGG2/EkiVLcPrpp+PFL34xjjzySOy9997GzmVuZEt1eB5cRwx5HsrIibQWctDzIHNzoUUoW+JKaUvQmu8MjWSViNnMHyEwF50H35/AhGmOaVrrktzMA7pLVHfnwXoeRiacMVPzhGkXvi3wxoS9wPNg2DA9kLbUkgVxmuehx8Oeh1rmPNjOg3H00kdvzAIV10OMWrsOOjUJUBu1DGDNno/HdZf/eOBxxxxzDH71q18Nff8JJ5yAG2+80fh5zU3nwWc2mrYEBJ2HYJdB35vKRbWO4HkIuxXBYKWSFyuVHBLnjHElCJqPqFYtW+IaDdM+8p8vSzlCiZnhibgh4ZwHtpKYEfFCz0O9aUsu+bbAGxNtmDbeeRCidZ2HaLAqwvdpb+KeB1sMmyKetqQblNXWipPrPMR/4ihD4kwyN8UDV5nKXJIBz8MIUa2er4fElZnzoD5qU0/14iHfMD3WhOkgbWnWB8WxPxnPAwBbPIxLcL2Luuc82M7DyKi/G4PAE+g82OdoHDiULZlNW1Kdh3ZGtarOgzrn3sTnPNjiwRRxzwPHzfBlmeC6J1qmNZ8GNTfFQ11pS9GE6epRrarz0K/kefClki2Vj2rNHxJnJm0p0gzOMpLrlS1pz4P6YbZ4GAfmmmVLQQHpEqtNAEtlPMlwoBPM6hsS58J2HsZFG6aFW4NhmlvWeUgzTKd2HuqYMN2uv1Ub0F0Gn0ftGvFEzNJAvGSgxn2Rc1M8SC5vMi6LIyhMVqgymdAJPQ8SZec8RJ4H7d8o23koSlsqf97Z5xYca8Y7D9HU4noWpETtMw9OK+Gch9o9D3bC9Kj48eKhlrQl23kwRjjnoU7PQzt20wdi2UPPQ3T/tBOm24V+mjgW1Vp9PTShToA+LwKsbGlCSK4jbUlEnoecyYTD3zdomGbHLeyMhJ4H5kqeB1EwkdKvcN7ZPyPWSZlhWHceapItAYAk23kwAWvZUl1D4oLnySEZziuwVKPvS5W0BNSatuTCD+fxWEbD99T7keOaHxLXuuIhHm8eS1vSn9fXWr0Tpm3xYIp4+mWV4JsQnnzngYPcpSaZn+JB1ut5qHLRJT0PTMFNLnfCNMKfo/wb5c4x7Dxk7FTwKC+WBPGuyCwjA89DnSlI0sqWzDChtCXreRidwc5DfbKlju08jI8MDNM1pC21rdsqBzwPgWEaTniN1dt5aFeh1QbisuvR5l415Hlo+C1tbqJa/RpkSx0n8jzoi65Md6PjDKYt6fQeNyfyaGCQSQX/RqhRzUxbGjz+KOjTnvXEJQ4XpPXV3D7ZnSUTyLplS/G0Jet5GInaPQ/hkDjreRgXDmRLjuHigYhaNzU5GggbeR58OOHn9ce8+/nIWNmSceIbs/5InQegbtnSAw88gHe96134+c8vx9LttscOXcY733YK/u7fzgAA3HLLLdh9992xdOlSHHzwwTjrrLNqPR9ggsUDEf1/9t49TpasqvP9rb0j69R59Tndpw9NP2loWpCHNtwjIvhAWkTUEfAKgnegcRh7uCN3HnfmKoMPHGd0HC8P9aooDig4AiIvZUARxGauT2gQodumeUhDQ58+fbqb0+dZVRmx1/yx946MzJNZGTsy9o6MrPX9fOpTVVmZEVE7IyP22mv9fusNAL4XwD3M/Bj32EUAfh/A1QDuAPBcZv4qWeufXwbw3QDOAngRM398kf1zSG+Emoy7LdnHgjIPTvNgamQeqo1MrH4jVPMwRzC9oFVrdVurijERJzoOlrKlViD2bktxMw9aNA+NKQyPypZiZB5KUbtkHhaFcy+Ybjd4AADuWSlO2RtpLPOgnPXwKANl6iKAAAAgAElEQVQRt2xJMg9toSsLs6b63tYmbtkSM+NZz3oWbrjhBrz+jb+Lzx47hf1HP4L/8aG/xic+8QkAwFOe8hS88pWvxJEjR6IdxyQpy5Z+B8B3TTz2MgB/xszXAvgz9zsAPAPAte7rRgCvXXTnITqBumRKlRMHbqB5mMw8bHex8Yfu6/Lq6jfKmu85bkuLWrUCo+zLquKtWqPZf6JattSPG+myUmaJomke7DmfkZGJaUPyInLmgQhGDTBAUWaIhWawK1vSLQumAYB6tpo+Wp1GGTyMZx7suRa3bKkfY9UHSidL1yQu/G2L2+fhQx/6ENbW1vCSl7yk3MtVV16G/+vGF0XbZx2SZR6Y+X8S0dUTDz8TwFPcz28EcBOAH3ePv4ntjPxviOggEV3KzEeb7t9waDQ5n7HMQ0BnQj0mmC5KkWy2TUdKXeoKXJ+HulatLvPART719G7HqtVvq/EmeoHxF+yYguk5Tf2Eenhxe7TMg//MwsjEtCHjmYc4nymmDBqFlJYtirsete22BABc2o/243M0ds/0mQdWI81DkSLzIMFDW6iJqo6Z79sfvwy4+1PnP56fs+mowZ7wnT/4scAzfmHbp9x66614/OMfD2C5rFq71jxc4gMCZj5KRA9yj18O4M7K877sHlsgeGgSUW5Ppgmbm4Xbvn2sXp+H6ZqH7V478iIOc1vSbuXVmLKDwBjtaB52iNtS7K7FAAy216gINfHvVSxxe1m2JJmHpuTGxM08wJbEDETzsDilTXX71z5SGWDQm9V0n2GnuZoHEUz3BUVOTxpQEt4FRMDP/8S/x203//9YW9uFj/7dJzs7lq6Dh1lMe/emXv2J6EbY0iZcddVVMzcYw6pVKyovFKPyn3qvA0ZWrWXmoUafB+M6Odfu8+C8zk2RTw0eQixmZ+6jkhVZZbhIYNWqtL2RSvCwGN6qNYts1Qojq9oNGStbihbkDZChKPvxCM3wHaYRIfPQtwnx2EJhxW1p6O4P0uehf2hFpZPlzHnirAzBvZ+z5+7hr4lybI9+9KPxjne8w/1GePnPvRIPeuBWPPEZPxhlf3Xp2qr1GBFdCgDu+z3u8S8DuLLyvCsA3DVtA8z8OmY+wsxHDh8+PHNHcTQPFavWALelss9DYcaCh+07TKPcTxEg/laV4GEaJqDcahbVHhSrjOH4bkssmodW8E3iRDC9vOSGoSh25iFDhlxKyxbFX49UBM1Dz0pxRiXKqGgeRvrH3Pg+DzE6TPdrrPoCEVWqOkJfHVcw/dSnPhUbGxt47WtfW+7m7LmNaPurS9fBwx8BuMH9fAOAP6w8/kKyPBHAA4voHQAE6QTqUs08hFh8TWoefEFRPbcldj0rah6j9pqHWYLp8e03YadoHsoxjOi2JE3i2oHLQC++5iGXiWkjovd5AACV2fdIskOL4QTTMa595WJMT1bTR9l6GgseJjUPcTMPcs1pE00EdpqHcG1s3GsLEeHd7343PvzhD+NrHn4Nfuh7r8c/+9cvx3/96R+Lut95pLRqfQusOPpiIvoygFcA+AUAbyOiFwP4EoDnuKe/D9am9XOwVq0/vOj+jWFkWbvRQ6ZVpUmcfazOiTfZ56GOYLp0BHBuS7U1D67Pg5nV5yGg3Gresa2821JsES5Q2vZK8LAg3qpVR7rEuQmPJlM2F2rbkGHVGdM8xBJMqwEyEs3DwvjMdYyypTl24svGWEPYStlSEs2DZB6ioMjNrZpUqDBHNVEBgEsvvRRvfetbkRuDf7jrJL52cDcG2ejedtNNN0Xd/zRSui09f8afrp/yXAbwo23uf1sVfUOyquYhIN21qOYhJHigOWVL3Irb0s7q80ARJ4ksbkvtkCDQA2lojDKPKnKjoFXDui2Vqy5xdqIzDJCLqH1BiOMJpvtWx19m68cE06rMOETt8+Dv05J5aBXlNA+GG75viUTW5O4xDHTuttR12VIyCl6sl8E0rFWr6zAdEJyUfR7yor7mwbvZcViH6cy5LfHMDtMtah5W/AbtxzCu25IED22Qohs4lC5Xzlf93I9BnqhsScPI+7MoZdlSTM1DPybE/lwiQhnwTM08xLr2kO5NoNUXFFGpJw2vWkp3baEpP3XFjgkemBltZxEzReVqQ4jFl9Z+sj2yefPbm/mayuo+B+hztFLIWc3VPCxScjFq7954E73Ai3Bjui31rdvqskJu/HSssiXAZR7GHVaE+oxpHqIJ222TOHl/FsN/nhDh81QGDz2ZEJfZ+qrmgXW5kBg18wDYz4rcH1rFui2FOVmOiCuYrlImnpagz8OOCR5iuC1pNdI8bGvxNYEPEnwpkanVYXq0uh/itpQpQgE9U/MwcluqtbmpVMXcK423/4zVtRi2qZXdl2QeFqHs+B4zeFAaitzigQhyg8nHmsRF+kxpcVtqhTLzECN46JdV61hvpFLzoCqZh4gdpgHJPERA0eweWvUs6LvIBLR3z2lis79jgocYHaYX1Tz44CHn+m5LpSNA3SyHIhTYLvOw+CrJTtM8xBRHsbgttYMP9GKKmCuZh6FMToPJCzMKHiJlHsiVLQ0luFsI8tcjsWqtCKYx1iTOn2PDmB2mAZd5kOtNmygi8BTNw/r6Ou67777tJ9fMSBU8EBEIZDMPLQUPzIz77rsP6+vrQa9b1iZxrRMyua+LVmR7NcAJJmtnA+zk0+T1Mw/+T9YRoL5GIXPBwzy3pUWyMlUnqJXGO/iIVevSQ6VVa8zMgyonvyt/7kcgiVWrHmCAc/L+LMgoeIiQeeidYJpB5DtMT8s8RLRqBeziVU+yNH1BEZVuS9Wp0BVXXIEvf/nLOH78+OwXnzwKZLuAY+fiHyiAYyfOgdUpDMgA97ZzXVtfX8cVV1wR9JqdEzxEcFsa6FHmgbn+BFwrAtGoa6fv/Zzp7ZrEVfo8BIh6Mq1QQAEzMg8+oF4seBjf1qpivAg3YtlS32wLlxaOnyUSzcNijJUtRRKXkh4gI3FbWhQyOQqoKI3PyjLQnlzzDPOoRLns85BQ80CqN4FWX/Cah8l54mAwwEMf+tDtX/zqHwAe9hTgWb8W9Rg9P/DTf4K3H/oNfG12N/Cjf5Nkn9PYMWVLIYLmulQ1DyEOSIBdlSg1D+5t2NaqtaIrCHJb8mVLc92Wah/6eewYtyX2gmnp87DseLelaCvawLjbkpTFBGMzD27cIjeJE83DYhCPmpm2jl8w6clqelHN/E/t82CQKWp9vlEigunWIYJzW2qwkGryqI1jJ/Gl6F3PEXZM5iFE0FyXMc1DoMWXVlRO6H3mYbuAYOS2ZL9qOzspssHJjIuNaB4CKFLYf3pPXgkeFsGXLUW9qJMuV86ly3Q4ecFQFFnzoAfIpM/DwigzHJVUtr3tnmkemHmUKJvWYTpwITEYEUy3ji77PDQob08cPNhqEt35HGHnZB5iaR4MO6FNmJtTphS4GF14gHkdpu1332F6mwqnif0QcuiZmQfvtrTIKkk1K7LKlB2mxW1p+UlRtqS0aB4WoDAGWWTNgw0eCskMLYjiHHmstcYy89CPCfGYI0+lSVyZeSg4nt4BkMxDBBQRCkbDDtNFnOaJM9BuTtf1ObBjggcTIGiuS1Yp1wkRMQNupb8Y1UtWtzcNf+yhgcooxTW7z8OiqyT+5as+f/KlMCpiKQwrCR5aIYnmQVUyDyt+8kcgN4yBip15sGVL8v4sBnERLfOgdb+sWk21isHkYFLgpJkHtfoCw8QoGulJg987kzZ4yJakbGnnBA8x+jy4TEEe2HsBsCcAm037erL2d9t2mK72eQj4XzJNMEyjGvAJGnVUnEDvELelsklcxBTlyKpVVpYWgg0KUNzmPZXMQy4r28HkhjGguJoHUgMMqJCysgUhk6OIlh3q1zXPuy3ZX/Ly3PW6msLwtuYnCyNlS61Tdpg2DaowutA8sAQPyTCRNA/AqJQoZPNaEeCsWrfq9HmoaB7CnJ2US3HNKFtq1FFxHNopmgdv/xnzxlDW/0rmYRGIi9KIIN5ONBSL5qEpecEY+Lcolo5INA+toDiHiVS2pHrWYXpsddrkYHf8vr9DbkzczIOaXUkgNMNrHjigJLzE5MkzDzm6DyB3TPBQVEVOLeH7NeTOHzjkgjHQCjDWqrVwF+XtNA+++mKUWqt7jFYwPSvz0EZGpmx6t+LzJz+GOmafBylbageTIHhQGhqu5lkmp8EUxozKlqL2eRDNw6KoiGVLqrzm9eMGcp7mwR2/vwbYoFgE032CiFAYX4nRJPOQMHjQCrmULaWDW1hhn8RP9m3mobnmYehEsvXclsLLltJpHlb7Bu0F03EdfCR4aAXmJJkHEs1DY3LDWPNlS7E+U3oNA+nzsDCKhygoUuZB90swbbjSub4SPIzZtm+zELgwIphuHa1QdpgOmicaY7U6qTMP3H32accEDyET7rr4SXduTLB2IFNUZh7KJnG1NA+ubCmoz8Psi01hwsqtph6bL99a8eDBr4zFzDygZ7aFy4otW4p4Awdsh2kWt6WmFIaRRdY8QLnMg7w/C6G4GGVFW6Z3moeqc2Nl1bkoRgsJ293LF0Y6TLeOdVvi8fe2DikswScYuS1J5iEJbaywT1LVPIRmNrQiKNdhegvzMw+qUrYUEqhopaxwdMaqDrfQedv/37ziwQMn6DBNSttJr2QeFiOV5kEyD42xbkuxMw8DDETzsDA6atlS/zQPY03i3PE3bRgbDGkJHlpG0fQO03Px9+lOMg8SPCTBtLDCPol3R8qLsFIi+9rRBNH7Z29r1erLlnyfh7plS3OsWhvV+E2gK1mRlcb3eYho/6mIlqIBTO9hk0TzQGXmYdVP/vaxmYfIlrp6DRlyeX8WRHMOE61sqV+Zh7F75jTNg+swHQ0RTLeO8h2mDYe5Lfn7dET79kls5kGCh2SETLjrkpVlSzxeB1nntZpAxRDAyG2pjuahYAYHdpguoAGe5bbUoB37BOV1dMUzDyO3pXgXCtsRXIKHRSE24CSZB3tOiFVrOGNWrRE1DxkMikI+T4ugUIwaWLa97TLz0I8Az5YNu19MDpqmeRDBdK8YuS0FunL6IC5p5kHZzAPQqcnAjgkeighN4nRZtmSCa+W0GkWOQ56fefDns5+k1L04zcs8BNf4TWHktrTaEyguNQ/xLhSKsO37JdSD2MDEbBAHjGUepCwmnLwwlcxDrODBflY5H8bZ/g4hbubBC6b7ETwUhseaxJWCaXdvHkqH6d5h3ZY43JWzg+BBK8KwDB66WxTZMcFDGyvsk4xnHsKbxCnjNQ/zMw9EBEXA0PjSmXr70c6qddaFuVFHxQnKkqoVnz95tyUVUQyniGwzJsk8LEaKsqVq5mHVT/4I5FXBdMTMA4Ayyys0Q6EAR5og6Z6ZRJyvefBlSyPzhPgdpvsRaPUFTQTmBn2vSs1DurKlTEvwkJQ2Vtgn8V0k84JRBJQSATZ4IJ95gLa/z3m9IipXN2q7LWmb4qIZJ1lhFg+qfM+JVXdbogSCadE8tAMhhWCaRPOwAEVVMB0t82CDB3YLNUIzMi7Akd6jLFMomMA9ueaZahWDK1saaCoXEHJjpMN0z1AKFbelHgim0X0z2Z0TPLSwwj7JpNtSiLVzpgnKjDQPdY5NKUJe+MxD/bIlm3mY7ba06EK6D3pW3m2pzDzE1Twsgw1b3yGTVjAtmodw0mQeBgAk87AoGjlYDaJs25fWzmpkumwYU8n8m8I2i1RUCqYLk6JsSRYr2sS6LXG4K2cHwYNWCkMjmYdkmMDMQB10pWwp3G1JQbELHkxW62Jjy5ac5iFIMK3KSc4kwWm6afuoNLBbaTh+nwcSzUMrEBJoHkiDWDpMN6UwJr7bkp/wGgkeFkFHzDxopWCgYHpyzZtWtpQpVck8pChb6sdY9QVFVLotBb11HWUeRmVL3Z0HOyJ4MIET7rqUmofCjKcya77WlxJtIat1sdE0yjzU/Vd8imtm2VKou8AUqg3sVhpftpTFzTxI2dLiEBfg6E3iRDC9CHnByBC5a7toHhaGmZGhiJp5MFAwRT8mxNP6PKTPPPRjrPqCdVtqonnooEmcJuRcOf86Il24NAMiegSA36889DAAPw3gIIAfAXDcPf5yZn5fk334FfG2P8+6UrZkDILKf7SiUeaBda0ayarmoe7KRh3B9OIdpkfbWml85kH6PCw91qo18gVdMg8LYSdZsTUPbsIrwUNjCmODh81ogmmbHdc9mRCPlbaUmQdCbkYljFo6TPcKRW4e11gw3VHmocMMVOfBAzPfDuA6ACAiDeArAN4F4IcBvIaZX7noPryQt22r1kyPuy0NAi4YmSJol0rfDNA8+LKluic4EcGQKic5k5gWUqzVBnarDLNBwRTdbWkZGsD0HjbgtrtCTlLJPAxXPu3WPkPDyJDIbUkE042x2pQCG5Heo0wTDKg3ZUtjpS2uSVzSzIMIplunX5oHwpa4LZ3H9QA+z8xfbHOjfkG8batWv7pQ+gMHdphWJgdAGBqqrXkoBdMBJ7iBnh08tKF58H0eVjt2KO0/Yy4q2T4PknlYFEIKq1YlmYcFGNc8RBZMi+ahMbnLPCBS2ZLPPHCfypb8/ZetYDpThKHv82AMdIh7SihSttQ6ZfBgAisxurBqVVQRTIvmwfM8AG+p/P5SIvokEb2BiC5sulF/Y2/bPe28DtMBZ91AK2geAnrNrlTUuNjoygUqJDjmbTIPbVi1+pevulUrjIEBtR6EVvE3Urk5LIbiAibWhLTciS7LB0TzEE5eMDTF1jxI8LAoRcHQETUPA6Wc21I/FkymCqa1Gss8DKJnHiTT2SZVzUNQ5sG/DynLlrTCFotVawkRrQH4PgB/4B56LYBrYEuajgJ41YzX3UhENxPRzcePH5/2lIrmIU7ZUrMO0wTFOaAHdmWnxnK27YLo6+7r74xJz3RbasOq1R/Lqlu1gm3vgLaF91WIfPDQjxvp0sIcXzBNGoRRYyghjKJq1RpLR1QKpuXz1JTcGAxQROtv43V5fbJqnewwbTUPzm0ptuZByeJS2xChLFta+iZxijBcAsH00gQPAJ4B4OPMfAwAmPkYMxdszfV/C8ATpr2ImV/HzEeY+cjhw4enbthbIi9bh2mbeRjU7kipaXSBCvlfzDbBQ8HcotvSik+g2GYeYpbSawXkLGVLi0Iw4NhWrZXyAck8hFMYhoaxgUOsD5ULHpRkHhrjBdPR3JZ0v/o8FFWTkTHNw2ghIa7mQQTTbaNV1ap1+TUPEjyM83xUSpaI6NLK354N4JamG47ntlTpMG04qI+EVgTNBaDXbEfKun0eGmgeGNpmOabQRv8LtUM0D+QyD233C6kigul2UGxgkrgt2c+udJgOp2wSF7O8zN3UFYtguikjzUM8t6U+ZR64ulBYsWr1Toi54biaBxFMt47VPLhKjB70edhaAs1D525LAEBEewA8DcC/qDz8i0R0HQAGcMfE34LwtfixOkznhsGB/RLKzIOqn3lQlQtUuOZhhlVrK25Lo22tMszxRbg2eBBB3KIQF/FKYTyufEBXShaE+pSZh5gpf8k8LExh4gqmM0UwTDA9CcALw9iVTWoeqm5L9RYDGyOC6dZRRKXxzfK7LamK29IODx6Y+SyAQxOPvaCt7fvMQ6wO04Ux1m0pqM+Dgh7TPNTJPIysWkNOcFOpzT7vb6GR9hRGbkurPYEiZpjIdfSKCAVL5mFRUnWYBhc281Cs9rkfg9y7LcXMPJRWrfJ5akpe2PeJdKzMg+qVSYThSubfBQ86aYdpyTy0jSKbdQiuxOigSVyZedCQsqXYpNI8hGw/0zQKHoqamYeKVWvICc40u2wptNxq+nG5IGrFgwcvmI6JItjMg9wcFoKYwbEvb24FUDIPzcgLhoqeebCr5ZJ5aE4+dCVfkVZXs56VLY0tuDnNw2STuPiZh35kafqCXbTjYOOb7jQP0uchCaYsW2p3u+MdpsP7PGTIK5qHGh2mK2VLQSJnUlAz3ZYCtzXtuEq3pYU2s/ywie7goxVhCA0UUqO9CApFfMG0zzxoVU4chPrYWnoTt7zMBw8zFk+E+RS5DbxIx+3zgJ68R6ZqMjJF82DLkGN2mCYRTLeMamrV2pHmIZfgIQ2+FrHtsqVMjwTToZ0JB2qUeajb58GWLTnBdIjmQWV2hW8KoeVW04/LbWvFV1+JC3uTi7kPImxyBuQSPCwCsUmUefCC6dU+92NQGIYmTqJ50CyZh6aYwgcPkTIPfXNbMpW5hCtbGlQ0D7kxGIhgulcowmJuS7F7ClXItBpVQEiTuLj4FfG2/fmzSuahCOxMqJXCADlYDWrXSGqqCKZD3JZIQSXpML3iEyjm6KvZWgFbnAHFZtT9rDoEBse+oFc0D7loHoLJjXFWrQnKlnqyqr2M+MwDImUeMuUmQz3J3lm3JfeLyQHSpebBmPCFxGBEMN06tkmcNb4JCx46aBKnnKkKIJmH2Pha/LYzif4CMTTGXlACNQ8Dst7ZdX2hqaJ5CDrBSc/MPISWW00/Liq3tdIkKFtSRNjAAMgleFgExQU4ZkMOYOS2pCXz0ISUbkuZaB4aY1wWNGbZkgH1KPNQ7TA90jx4tx4Akfs8SOahbapuS800D+kyD7bMz+2vw/NgRwQP0TpM+8xD4U+6MM2DzTxktTtSalV1W6p/nOyDhymZgbZWSXx791UmRdmSIsImD8ASPCyEgkmYeVAimG5AbpxgOmqfB8k8LIrxmoeIgukCCtyTCbFhnnBb0qVpQlHen2N2mBbBdNsoInBfNA/a9YKq7r8Ddkbw0KArcx38SZa7VGVIKVGmyHbt1PUzD4qokdtSGRVPWdkpQt0FZh7bTnBbiu/go4iwhUwE0wtiy5bSuS1J5iEM43vjwLSfEq7iVsszSOahKSPNQ8zMQ3/Klky1tGUs82DKRQTpMN0v/PzFmMC5VUduS1K2lAh/X2+7DpGIyolDqMWXVoQ15GAa2NrfOoLphm5L5QrslJWdNjQPgO/QuNoTKOIigdsSsCVlSwujuIgvmK5oHnznd6Ee3vhBx+7zQISCMmjOwSt+fYpFkdsJisriCqb7Usdv3Zb8L77Pg8s8+Ptz9OChH2PVF7zmwVT1LHXoyG2pEMF0Gooy89D+tv1FIzTdlbmypUKFNIlDxW0pJPPgTuwpJ1qrwcOqr75y/MZj5MqWyAx7sxK3jBBMmswDgIxYMg+BlNfk2JoHAAUNMEAhpWUNMYXXPKxF2b7v89CXCXGpeWC2x+z7PBRc3p/ruCc2RgTTrUNEMAbB5eddNInTSknmIRWxNA+AtVwtjAm2+Mq0smVLauCaytTQPIy5LQUcpJpdHyeahwAS2H9qRTbzAIjj0gKoVG5LANY0ZGIaSF4NHiK/T6wyu1Aj71EjvOZBRXRbKrg/wQP7EuVy4pgh06p0XQRQ637eGBFMt45WNnAId1tKn3kYaIKRPg9piBk8+MxD6EmnFWFAOQxlYZqHJvoNcif2tLKlQIvZmbug1e/zoGCSdJjegnu/pHSpMYojNx8DyqB8TUnmIZSyvCN2kzjYzMMacgnwGsJO8xCrbKlsEteT1fRSJ1hx2vEdppNoHiTz0Drebcn/XBvRPKw2sTQPgM0g5EW4xZctWypgfJ+HWpqH0c9B/0spmD6/DCbYXWAGWtHq1xRz/FIYRYRNn3mQ4KExCkX84MGtmA+IpcN0IHnCsiWjBshQlAGLEIYXTEfLPGhfttSPz1B5z6xMHL32MZnmATzVPVFoRjVg6IPmYeiDh6I7I4gdETyMOky3v+2mmgdv1WpUhsJ1qZ1H9QQPujap2VFqcI3frF0QrbzbEiXq87ApZUsLQ2CY2GVL7nO1poxkHgIpV/kSZIhYDTCgXAK8hnBh7xux+zz0KXggGg8eMjcPyFNoHkoDlH6MVx+ozoGC3Jb8e5BY87AJpz/qcIFxRwQPfkU8SubBaR5CLb4y12HaUECHaVUNHhpkHqaWLbVTzmXdlhbezFJDHL9sSSuyHaYBIBe71qaoBOUw/iaeKZaSmED8JCtN5iHDmmgeGuPLlnQWSzCtUECBelKKY9i5HVY0D1op2+/JJMg8qO6ddlYN3bSqwweQse81FTJVrU7YSLbfSXZE8NColq0m45mHsNcNUKAI0DwQNQweaHafBxPaUXEGinZCh+n4vQMUobKq0N2Foe8kCR585kHcloIZc1uKLpgeYCCah8aMNA+R+zz0RAQ8VfOgfeYhUYdpoDfj1QeoaVWHs+qNUtYyA99hmklL8BAbf8+IETxU29IHuS15q1YK6DBd2XxIdEzblC21qXlY+T4PKOILphWNBNNSttSYNJkHu/2BYgylnj4IP15pMg9ryFCUTnVCGMaVLSkdt8M09aQMp+wwPaF5yI0Z9WGK3WEakMxDizSu6vDBQ0J8YGr0Lilbis3Iban9bWvn7xzstkQGitj1eQjXPATFQf7knnJxLkI7Ks7aBRFWvU8WJRJMl1atUrbUGMUmgVWrCx6IUUg9fRDjmodUmQd5jxpRZh7ilC2Vbks9WUk33pb9PLeliuYhumAaonlokerbFdznIXHwoMvgYV0yD7ExETUPA62wVYQ3btsFe6HMWcNwPYGVqhx/UOZBz24Sx6EdFWegFFbebYmYgdgdpl2TOACSeVgABU5WtjQQzUMwfpJFCTIP0BnWSDQPTSk1D4M4wcNAKxgoUF+CB98baUwwrcA8yqilEUz3Y7z6wLjbUmjmIZ1YGrAOnwBQ6DUJHmIzcluKo3nYyn3wUP91GeyFJ3c9GOp2mB793E7Zkrgt1YdQRHfwIenz0AoqRYdp3ySOxG0plLRuS2uieVgEd9/QkcqWFKFXZUsFu95IY03i7D10M7ePxRVMz7ZeF5rR2Mmyy7IlJWVL0fFz2lhuS2XwELD9AdkL8pC1O7YamoeGdXm0zUpFmYJdEL0j3JY4ulXrWIdpCR4ak0KI62/imYLU0wcy6vNQRF+5Y+36PKz6BZY2ywsAACAASURBVCoSsd2W7KJef/o8MLNzWxqVLfl78+bQly3F7DDty5Yk89AWY3Or4MxDN2VLhdolmYfYjNyW2t+2VoRhg7Iln3nwtpzhbkshBzm7bMmEtmOfAe0AtyVCkUjz4AXTonloii1biq158E3iJPMQSpkNTqB5gFqTDtOL4ATTOpLbEgAY6lHmwS+4cSXz4IMHt5CYJvMgwUNbNNc8dJB5cFkuW7YkmYeojATTMTIPI81DiHYgYxc8uIlirT4PDa1a1TYXm1CL2Zn7oB3gtsQMTuC2JFati6Nhxluyx0BJn4em+ExNKs3DALmI2ptifOYhXvDA1C/NwzS3JWBUtiSC6X4xpicNFUzHXvyYIKtmHobnku67igQPCzKueWiSebBvQS3BdEOrVn9z5mmah7bKlpxl7SpDCeroFQGbLJqHRTCGE2ke3GeXWJx8AimbxHGCm6/TPIidbkNc8EA6TtkSADDpXmQeTLWKwXSUeRDBdOs0drI08csuJ/El7oWSzEN0TEzNg6ZGbkuZ++BvGK95CHNbCmow7dJqRXF+8MCMsBq/GdCO0DzEn5DqqlWrlC01wjCn1TwQo5CJaRB5tWwpcoaI9QAZieahKVxOkuN9npg0CMs/GS6dG8/TPNhzeGPoMg8x3ZakbKl1qtmGcLelbgTTOYnbUnRiah6yMc1DwOtgV3M2jbd7nP9WNLUT81atZkrwULTUYVorrH7ZEkz0siWi5Wg932cKY6CJQbHLlrzbkpQtBeODrRSaB8pE87AI5ATT0PHKlkDKOm8tOd5RcLJsyQcLG0kE0z7zsPzj1Reqi7F90TzkHWce0v7XMyCiOwCcAlAAyJn5CBFdBOD3AVwN4A4Az2XmrzbZvql+4FtGK1WWLYVM6DO3yrLB9TMPi2oepmUejHeOWJCdoHlQKTIPSprELQq7kpjoTeKqmQeZmAZRZh4SuC2RHiATzUNzKpPkWHBPBNP+FjfeJK5atpRA8yCZh9Zp7rbUXZO4XNyWSr6dma9j5iPu95cB+DNmvhbAn7nfGxFXMD3SPIT0kdDsMw8BmofKuxVk1eozD/n4xYbZdsZur8P0ak+gCJxE82Cg7MRXmsQ1oijceZ6oz0NGRjQPgSR1W9Kuz4OUljWCykly3MwDYfk/Q2NVDFMF0yk0D27bPQi2+sJifR5SC6btfS0n6fMwi2cCeKP7+Y0AntV0Q/6+3sYK+yRaUynEC8o8OLelDVPfbanpCa60zzwMxx5vUwuiaLQqs6rYlbG4fR78qofR3V4Y+oxxN/XoZUvKC6YNDK++VXGblB2mOUHmIVuTPg+LUKntj0VvBNNcuddXtCB+Qlf2eZAO072iudtSd30ehko0DwDAAP6UiD5GRDe6xy5h5qMA4L4/qOnGfZ1ihNhhvElcyIS+DB5UuZ25r2lZ89CmFmQnuC1ZB5+4Ex3/HnPHHs59xmfYopct0ahsCcDKd1hvk1HmIb7bEukBdlGOvFj+yekyQiZHDh3nBlruRNuGgUuOX4ikibKlSatW6fPQL6pvV1AlRqeC6YFoHgA8mZnvIqIHAfgAEX267gtdsHEjAFx11VVTn8Mcnhmoi1ZN3ZbGg4fQDtMhJ7h3WzLF+MWmTS0I7QDNQwqrVr/qYdSalC01xLAvI0ykeYALHgxjkDaD3VtKzUMxjCvExchi1ExkXoV6ENvgIeZkgXsimB65LWEUPJA+z6o1jWBagoe2aO621J3mYYvWgPwcXO150mMAliTzwMx3ue/3AHgXgCcAOEZElwKA+37PjNe+jpmPMPORw4cPT92+X3CKpXnwBImYXfBwtqifeahuvknmYVIw3aYWRO+A4EGxif4h9W+r0WsimG5ImWFL5LaUkb3ADGVluzZlk7j8LLC2N+q+KLPBQzGUYLwRJkeB+Fm8XmgeZrgt6dJtKWXmYfnHqy9QrzQPrmzJN5PtyNK98+CBiPYS0X7/M4DvBHALgD8CcIN72g0A/rDpPkYr7Asd6lSqGYOQC4YXTJ/NfeYh1G2p9q6g3ck9ufJWah7aEEwrrH6fB3D8siWveejYSaHPmMqKYFTc50q74GHVy/baxDofMWh4Dhjsibovn3lgyTw0QpkcReQiBVYaCrz0wrmxBbcpTeJGVq3SYbpPNHZbSqDZmmQs8wB0Nk9YhrKlSwC8y0V+GYA3M/OfENFHAbyNiF4M4EsAntN0BzHdlgYVYVTI5rXr2llmHmq5LTXMcmT2beaJsqWy7riFYdkZbksGseNt/74avSZN4hpiylRjGs3DwGkepI9AfXLDWMcWCAwMdkfdlxq4siXJ5DWCeIg8kX4IpgD0MkxLpmOqVQwVIXkpmM4TNIkrgwcpW2qLaryw7H0eiMj2FyNv6d5NRrXzTykz/yOAr5/y+H0Arm9jH94FJYrbUlWlHxCx+rKlc2XZUliTuKDgwQumzXjZUptaEEVUbm9VUSk0D27zpuMGMH3Gd8RN5bakaaR5EOpRGMYeuPM7ctmS0j69L5mHJpApYCKXLZWf1SVfTR+5LWE886ATah5EMN06fXJbAuycbZN22V86yjx0XraUAn9PXyrNQ5l5qN8krvqUoEBFzxJM++22oHlQtPplS8zRewdQVTAtwUMjkpUtec2Dq9WWzEN9csPY7YOH2GVLTvPAknlohOIcBUWeIPVkNd2Uzo2z3JbCnReDEcF06zTv85C+bAmw884hd5t52CHBQxrNQ3C6C8CZ3L6mTo3kWF1ekOZheuahtGptqc/Dqq+8ahTittQDuPBuS7EzDxOaB2lCVpvCMHaTzzzEDR6UDx6kDLARNnhIWLa0xEwvW6p0mB4WyBS10nh1JpJ5aJ0xPWmQ21KXmYduNQ87K3iInnkIeKG7kfmypTqZBH9BIgq0ai01D9PLltpYJVE7wG2JwNFXs/05WkjmoTFcad4UlQm3JekyXZ+8qJQtDSKXLQ0keFgEW7YUeYKk+rGaPr1sSY9ErLmJ67QEiGA6An3SPABAphW2IJmH6Hj9ZKw+D9N+nourvz2T1xdM++g4NAjS2rstTWQeuD0tyM4JHmJ3mLbfC2kS15ii1DwkcluSsqVgcmOwJ1HmQbs+EpyL5qEJknkYUYy5LVUzD14wbeI6LQGVsiUJHtpiTPMQMivuMvPgg4fhueT7B3ZI8GAid5j2BE3qXfBwenj+dmbhnxI62fdN4tiI5mERdMIO01K2tACl5iFNnwcvmM6lbKk2uWHsV6kyD05YKJmHRijOYRLZHi/7hJhnBA9+4XBjWMTPPPgVpiUPtPpEdQ4U1mG6O83Dpmge4hPTbSmrhKlBtXLFFgoonHXXn1puS2pUthSCGriVt8kmcS1qHohG21tVCCb6hNTfeAqSJnFN8VatpGNPeFzWENLnIZTCMPYpt3IS2arV93mAkcxDExQXMJEF09STOv5ihuZhUGkSNwhaum6ACKZbp/qW9cFtKdOVzINoHuKRzm0p4IVmiBy6dGeo57ZEtZ87dox6VuahPc2DzTys9uRJJQge/HuRqzVpEtcQ426qlKjUQonmIZi8YOwlFxxHLluC7rYTa9/RCdyWRlatyz0hnmXVWnVbip956Eeg1SfGO0wHZh5i32emkCmFDRbBdHTGWsq3zJjmIbBsKUdW1knX0jy4dys0CBr1eZjeJK6tPg/FqgcPzNHdlsYE0zLZaYS3JI7f52Fc8yCZh/oUxmBvorIlaL9CJ5mHJiguwNGtWvtRtjRqrOozDwQoVVYO5IYTaB5EMN02425LAS/sUPOwAR88SNlSNJg5mu9yNtZhOix4GFYcLEIyD6H/i3ZuS5gsW3JznTZs5RQRVn3hVcFEt/8cBQ8DEUw3xQfJiTIPIpgOJzeMvYkE0z54ICPBeBM05zCRJ0h9KVvy62PaBw9+AaG6iBizuzQgZUsRaNqA12oeOihbUoQNdvuVzEM8CsPRUonN3Za2xlLBIR2mQzMoWbZ92VI7bkvYEWVLHFkcNaZ5MEOsfEQWAZ9hI52msZWGdJgOZazDdBZX81CWLU30uRHqoVBEN4roi1VrUe0ZVVl1rmYbonaXBiplS3JvaIvqWxY0j6sEkCnRirAhgun4GG5ndX0azTUPOfLgzIN7brBVqw8eJjMPonkIQVOKDtP2e658nbZkH0LxQXLURk1AedNQLvMwLORmXpdhwdhDW7a7dOzJlgseSMoAG6E5TyiYXu7P0FjPqMqqczXbkK7Pw3IHWn2ieYfpjgTTinCORTAdHROxbGmsw/RCmYcawUPpthSYeVCEIevzgoex+s0FISKs9NzJB0aJypZy6nZVoc9wMRIyRqXMPIjmIZTC93kYRC5ZAkbnQSGahyZoFOnKlpZ8Qlw6FE6ULY1nHkQw3TeaW7V2qHkwUrYUHWM4ik0rsEifhy3k1EzzEOoEpxXBQJ13sSnrN1u42Gk18sBeSco6+oRWrYCIphvATkioEjWJU6J5CCY3jN1IFDy4zIMSq9ZG6ASC6b5oHkz1nsmVzEPT8uUmiGC6dRpZtRoDgDvKPCjkzIDeJcFDTArmKDatwLhgOsxtKUfhfXqBWt7QI8F0qFUroYA6T/NQmPbKllbdbYk5jQjXv7VD1a0NW58pO6nHLodx54L0eQin1DzEFksDFc2DBA9N0MjBkSdISvcj8zDK1mNs1XlQudZk0uehdzSyai37fHRg1arJnovZumgeYsIcx6YVGM88BM3piy0UlYloncNratWaKYV8SubBtGhha92WVnfyNCqFiZx58G5LZdmSZB6Cced5qswD+Q7TK3z+t01uGOvJMg/2sySZh2ZkKKIbRVDPOkyP3JZs8KAUlfd/KVvqH42sWitNAlOjFdn7TSaZh6gUJo3mIUylPywniJmiWnV2/jmh81dftjS7SVxLwcMKz52KRGVL/r0Y+uBBBNPBGD8BiR080GSfh+We+CwThWHsxgawFrnHA1CxapXgoQmaC0AN5j9xAXzw4Hu0LCtjPaNMMXaN8UFD/LKlfgRafaKRVWuHwUOmXOZhIJmHqBiOZ9XaXPMwLAXTdY/NR8eh+o1M2bKlyTRnWb/ZQvCg1WpbtZb2n7GDB+UF07vsA1K2FI5/r1JpHtxNPC9W9/xvG9E89IcMRTK3JbPkdrr+nqkmMg/A6D4umYf+0ciq1c+nOrFqVfZ+k61L5iEmhjmabeO4UCrghcUWiike0duhGpYtaUUooM/zOW9d87DCqQfjraQiax78e5FL2VJjSqvW6JoHu30Fu79VPv/bpjAG67yRRvOgNAooKF7uiemyohG/ERa57RfFcr9HpnrPnAgefH+H+JkHt33JPLTGuNtSzReZRK5+UygzD9kuyTzExJh2VtenMa55CMs8mMDMQ+MmcT7zEFPzoAgrnHgoMw/RNQ9l5sHbS0rZUihcah5iW7USQGrU50GCh9oMC8Yu3gQGCcqWAOTIQGLVGgwzO81DZMG0W70tlrxsqWysqjrMPIhgunXGFoF7IJjWmjA0RjIPsSmi9nloXrZkvOahZspi5LZUfzeAzzxMKVvypeEtdZheZbcln06PXrbk3ost6fPQmGSZBwAgXQYPxUo3OmmXwjB2YQMYRO4u7fdHGTRL8BBKbhgZ8nSah3y5Mw/FWJ+HWZqHVB2mJXhoi+oUqFeah2wdGErwEA3DHM9tqTLxD8pumCGMGgmm6+ADldDJPpEVTNOMzEMbznKaVrvDNBdpRLijJnFe8yDBQyhsfJ+HBBd1paXPQwNyw9hlEpUtwQYPSoKHYArD1opYx/0sae0zD8sdPGynefC27QMtmYe+Me621IfgwWsexG0pKsZE7POwgFWrL1uqrXkg/z38f5mWefCZgrY6TDOvbqO4dG5L9vvQ9wCRJnHB+J4cSTIPeq0U4ormoT5cDLGGYdKyJbXkYtxlJM9zKIrfCItccGKW3LFsVOoLO3mkauYhkeahzDws91j1iXG3pZovWgrNg7gtRcVwvA90486SRV5mHnTNlYpRh+nw/2V6h+mKZ/WC+GNa1fkTJ3Lw8eM49JoHyTyEk6rPAwDsPgi1cQKAZB5CyAq3WpYs8zCQsqUGFEM3Zsk0D8sd4JkZfR6AlJoH6TDdNqrJPK5jzYP0eUhAwRyWFQig2mE6TPOwBVO6LcXVPACAIX1e2VLRsubBbnM1J1Cl/3jkzIPPAg0hHaabUq5eplgR2nMI6ux9AFb33I/BoDjnfkhXtqQl8xBM7hYvSMfVPPgO0yZf7lKcUYdpr3moui0l0jyUwcNyj1WfqM6p+qN5MEC2e+dmHojoSiL6cyK6jYhuJaJ/7R7/GSL6ChF9wn19d9N9MHMSt6Wga0axBfaZh1DNQ6PMg57S56GSgl0QVWYeVnMClVKEqxVJ2dICkDvPdRtinnnsOQScs8GDZB7qMzA+85CmbEkE080wuR2z6G5LZdnScgd4/vY2clsarTqnyzxYlzcRTLdHI+ObHd5hOv1/fT45gH/HzB8nov0APkZEH3B/ew0zv3LRHRQRNQ/VVYagfZh85LZU82LjN9/kfzFQ5aSqfKzqHLEgfhurGjyU3YMj93kA7CqIuC01h4tETeIAYM8h0L2fQaYIubgt1SYzPvOQyG1JDaCWvCRmGcld8ECRBdOjDtPL/R6N9UaayDz4CWjdMuSFoPMXA4XmLKR5SDAnmMTeb7rVPHQePDDzUQBH3c+niOg2AJe3uQ/D7fQymEZ14h+U3Vgg89Aki2JII5vVYbqFsdFl8LDwppYSTtRhGrAXsi3RPDSGXS0wJSpbwtn7rR3yqp78EVjzmodEgumCBsikSVwwptQ8rEXdj3dbMku+ml5m67dxW4qeeQBsxmPJx6pPVIOH+pqH7gTTWqlKkzjRPICIrgbwOAB/6x56KRF9kojeQEQXNt2udVtq4QCn0CjdxQwUQ7AOyzz47TdJFBia7bbUxtj4Y1rVCVS5IpZgNVsRoWBtVzSkSVw47jxXqcqWtk5jjxpK2VIAA595SCSYNlK21IjCdbhXkTMP3lZ52fs8jDVWPS/zkMhtCbBlSyKYbo3qW1bbfbJDwXSmCLlvEmeGnQSSSxM8ENE+AO8A8G+Y+SSA1wK4BsB1sJmJV8143Y1EdDMR3Xz8+PGp2zbM0T7QY4LpuqNpCgBcNt4JbRLX5H9haNDExYa5vbIlf0yratXq/69UmgfD6LT1fK9J1WEasMEDgIvVmZUNnGOwi33mIVHwoCTz0ATju3LHDh6yvmQe7PeR29Jo4jhQvs9DmuaUEjy0R1nVETK36lIwre0cwWjfDyp99mEpggciGsAGDr/HzO8EAGY+xswF2xqE3wLwhGmvZebXMfMRZj5y+PDhqdsvuJ1eBtPImmgenC+8CSxbWqTPgyENdZ7bUvuah1WdQJWZhwRlS0RuHPWaBA8NGDWJS6N5AIBD6rRdCRJqsZZYMG1UBi3BQzCF0zyoyG5LfSlbGtc8TLdqTZJ5UCKYbhM/Pwx66zp2WwIAzrprJtt58ED2XXs9gNuY+dWVxy+tPO3ZAG5pug/rttT8GLejUZ8H76Cjw5rELeK2xKQAxNM8jNyWFt7UUpJyQqoV2UxHti5lS03wTeJSlS0BOEQnVzZwjkHyzAMNkEGCh1DKRZPYVq2+bGnJJ8Q8VrbUoeZBBNOtoxUFmt50q3kAAKO6s3TvXDAN4MkAXgDgU0T0CffYywE8n4iuA8AA7gDwL5ruIKbbUqMO04W3v7NvfN3Je6Po2LGd21IbQ+OPaVXdlowfu2SaBwayNSAXq9ZQuIOypUN0GueK1Tz3Y7DGGwAhneZBDTCQ4CEYU2oeYmce7GfVO6UtK2PZ+i41DyKYbh1F4Y6Z9oXdaB4AoNC7rKn7TgwemPkvYG8jk7yvrX0Y5mhuS2OZh7onXllHaoOH0MxDE7clJg01o89Du25LqzmBKu0/k1i1Os2D3iWZhya4WuDYIk8AZfBwIZ3Cack81Gad3XmdKPPAaoCBlC0FY1yWPLZVa1/6PGynefD38TSZBxFMt40i6o3mwR9nodbtAzuxbCkFxrTjKDSNsSZxtYOH8bKluh0p/a6a6DeYzhdMFy0Kpldd8+DLllIIphW5rFCHHs69xpctJXivsNuawF2IUxiu6LnfNsyMXbxhG1fquBagHqMG0JJ5CKZw7kepNA+85KvppjTOwDaah1SC6eUeq76hiMKqMDoWTANAobsrW9oZwUNEt6Uxq9ba/sC+jjQs8zByW6p/fB4bPEzXPLQSPJRuSwtvailh956lc1vyZUsSPARjfIfpBOlknQG7L8RBnBw1EhS2xTCwB5sY6vV2aiZrwFK21AgufJO4yJoHn3lY8rKlMlvfdeZBabsqKrSGVoGZB+5S8+AzDztYMJ2CguNpHogImaKwzIZPBbuTLqup5lal5qFZ5kHP7DAdvLkpx2a/r2rmwZSZh0SaBwNXtiSah1BGosZEF/U9h3AQp2zHT2EuuTHYjU3kOk13aQBglWGAvLzmCfXwgmmVxQ0essxpHpY88+CbyE/TPHjL9br384WY0rdJWAwK1jyk00FOMnCLmHmHgukdETwYbmd1fRbBEaufEDqbrVRuS4TxlYpWNQ+l29Jq3pw5ZfCg3AS4w+6RfYa8YDqF2xIA7DmEC/mBlQ2c26YwjD2UOHjQaxggL0s1hXpwkUow3a+yJTWlbCm55mHJx6pvhLstdSeYLjMP5DIPQwkeohCzwzRgLxZBOgS3muNTwaGah6aZBzWpeSjdlhYfHFpxwbS/UMfqF1Jl5LYkTeIaUXaYTpd5uIBPSYfpmuSGO8g8DDBAIQFeIOz6PFDkzEPptrTkE2Iz5rY0XraUVPOgpElc2ygKrCBZAs3D0PUKk8xDJGJqHgCXeQgKHrxg2nWYrqt5KN2Wgg4PAMBKQ030efDz/Hbdlhbe1FJiEtp/6tJtaU3Klprgbqo6WdnSRbiApc9DXYoiffAAZTMPEuCFwW6hS0cPHlzmYek1D/b7SPPQVeZBBNNt00u3JfJlS6J5iEJhOOqKcaZVYMTqRWiuz0MizcN5mQcWzUNd2I9dglUlGnNbkrKlYHyWKMVNHLCZB3MS+ZJPfJaF3JUtmSxl2VKGjAyKoYimQzBOMB09eOiL5sG7LYHt5L2zDtPS56Ftwvs8dCeY9gHqsBRMS+YhCszNeiPURSsK0yE0zDz4/6FRzwrSoPM6TLdo1brymoeEmYcxtyXJPATDBXJWSUrMAAB7DmGAIbL8bJr99ZzcGOzBJoqEwYN3thtKGWAQ3m0puubBBw9LvprObEugCd6qcErmIYlgWsqW2sbO4wJe0KnmwR7okMRtKSoFc9QF4yxUaFM6WIR2mLbfm8QOrDT0xMVmrH5zQfw2VtU9biSYTqR5MCxN4prCBiblpW3PxfZb8UC6ffaY3JUtFTpNgzgAYDf5Na6GX6gHT9yrYpG598fvb1kpDI/0DsCE5iFhh2nv9iS0htU89KNsqcw8kGgeomIiWrUCzd2WqGmH6YaZh0nNg2lT86D8Nlc18+D7PCTsMC2C6WawgZnatD4Srsv0vvxEun32GO+2ZAbpMg/khIXFUD5PQbgS29hWrdrdQHjJV9MNuyz7lImjzzgk6/Ow5GPVN5QKrFBZAs3DUDQPceHIVq2DUM2Dt78buLKlmpaS/n9oVI6hNNQMq9Y2rnWr7rbEZWfR1FatMtkJhdigSJp5cMGDkcxDHXLDWMcmTJYu8+DLloqhlAGG4DMBWeTgYaAJOS+//agvW5oaPJSCaekw3Uf62GE6h7bngmQe4lCY+G5LTdJdKrTDtHu3mug3WGnoyeDBMIjasR/Vqx48lJqH+MGD9latepdd+VvVWrBYmAKcNHi4CACwT8qWalEUVvPAg3TBg7caNZJ5CMN4wXTcsiWtCAXU8gumDTunpfPFsv4+XtcAZSFEMN0cZuCD/xF4+4vHHtbBbkvuvkzpNQ8+QC06NFbZEcGDYQ6LKAMJ1zy4zINrElf3hB25LYUdHwDQjLKltjIypeZhNWOH0U0tQfBAZdmSu2GLXWsYyTUPPvNwMt0+e0yRbyAjk9RtyWcejHyWwkjVYVop+5ld8tX08p65jeYhnVWrLCo14i9/GfiLVwO3vB04cWf5cHiH6RwAJXFgnMTPGXPTXTPZnRE8+NWCSIRrHnzjnUDNwyJuS1MyDwW3Ny7+87PqVq0qwYVCKxpZtQJi1xoIwaCghJe29QMooHCBlC3VgjedK1XKzIMvWxL3sjBc5iF22ZIi9CLzYJjnah7SCKaXv8RrKfnU24EPvgJ4yDfb3z/3gfJPjSpIOihZAkZzxsIYyTzEpM0V9mnYDtMBLyjGRWj1O0w37/MAmuK21GJGRq142RISli0pcuOoJfPQCC7AKQXTRDijD2K/ZB5qYbbOAEDSsiVvi80SPIThJsl6ELdsiYhs5mHJJ8RmUvNA53eYTqJ5UEoyD6GcOga8+18CVz0J+KfvAA5cBXz2g+WfFTWwau0oeCgzD0V32sgdETwUfrUgEsGZB+9gMWioeWiUecigiEdtpeEyMi2Ni9/Oqpbne6tWpdO4LRU+HQmIaDoQMkXasiUAZ7KDuECCh1rwls08pAwevNWouC2FkUowDdjMw7IHD6V+chvBdJrMgwimg/n4G631+TN/FRisA9c+DfjHm8r7qyIKdFsquss8eMG0YWCwWzIPsSgdEiKRKdVI86C1zzyEaR4aZQv8innl4tyu5sFvczUzD2XzogTlMIrIxnhl2ZJMeIJgTuu2BOBcdgAHWcqW6sAu84DB3nQ7dVk8lj4PYZgcBRN0gkUTBvXCqpVmCKZHmQcRTC8dxRC4+Q3ANdcDh66xj137NGB4BvjiXwGwi7NB5jEm76RBHDA6x0aaB8k8RCG221KmKdCq1TtY2JXlQU13hrLPQ4MJv7cYNcXo5mkb3gRvaio+CClWNHjwF2qt03SYLsbKliR4CIE4sdsSgHODgziAU0n32VuGNvNAawkzDwMRTDeB937D6AAAGSxJREFUzBAFdJJu7YYUaNmDh9Jt6XzBtLdcT9dhWoKH2nz6vcCpo8ATbhw99tBvtffYz9nSpXC3pS41D95tqTvNQzf/eWLOW2E3xg72mePAqbuBzVMAwa0qk13a9z8DNlNQDO0krhiOLhyObz33eRzNM+DYYeDCq4G1OStqxRAghWxgh7+u5mHUYbqZYBoAzJ0fgTpwObBxAo+6/y9xlu4HTjwKOHilHZcz9wCbp8saYZw+Bpz8ip08Z+s2RTbYPYp2N08Dmydx8d3H8WL9KVx168eAu9ftwepd9jXZmv2u3XdSwNZp+zXYA+y+yD7/zHHg3FfdYxfaxzZP2/Hfc5Ht5Lt5CnjgS8DGSWDvxfax/Bxw9n57vPsvte43575qLxbFlj1WvWbf83zTlm6Rsl9K2++7DwJ7D9vnnTsBbJ4c/V1lOHDiNvcexJ+Uktc8+LKlT77NrpaQGp1/pqjU3Vb/Fxr9Xv2a1AAoDawfBNYP2P/11FFg44HKa2ZsSzlfaZ3ZbW6dtu9R0xsZaft52bXP/m6Kyv+Yj9f1MgOolt7x1Mcu2fjH5GVL57KDuJrvA/7yV+znY9p5ojL7VWyOzuv1A/ZcB+ykuljilXGlgWy3vTYUW8DwHAAG1MCthObuvStsaSaz+5915fnAxV/6rN1eyuDBBeIH7vwQ8KkNe27nW+7a7r7YVO4BqnIfgP3b8Jx73jYLJOW1mca+jX6f/Ps2vyvtrp/r9hq3ecoes3KfT3/tGvu58hn1/0MxtJ/P9QPA3ge5ModNez0sttzPm/a8ZLbX1b0PAgbr2LN1H4bQiKt4sBho7N86Bnz+Q/aBtf32upBv2v9daXt/3fdge36duRcA23vAYD3BEU7RPHTW50Gtbo1wDD7yW8DBh9hsg2dtL/CQJwOf/VPg6T8HosBF4GXSPLhra0pWKnjY2jiLL33mE6MH2EBtncYTi4/j+rveC/zm3wHHbj1v8r8oL/E/vPbn7UX7mm8Hvu55wKVfP73G6PQxQK8FpzlLt6UGscPWmp2gZL/7feVjz3Vf+KVfshPnzVONI9grAfzUAMAnG7186Xk4gIJpNMmNiFaEc1sF7uSLcYUagP7yl6Lvc5W4EsDN6utwWcJ9Htv/tThy77uAD/xUwr32k8sBbLGG2X95sn0Wey/BkDUuv+31wG2vT7bfvvNYAMdxECkKzE5jDx5x8q+B3332ts9jlYEm7uHF2gUYHnwohgevAbhAdvou6M2TMIO9MGv7wCorAy12QRWrNbAewAz2o9hzCDzYD7V5AvrcvVDDs0CxZbOYag2s11DsvgjfcJSx1+wB7rzC7nhK2VISzYPSwIkvAm95vg2uLrgUuPChdhFsagDsFkUnF0epGrROPEdldoK9ts8+n9kG0f7LLayh2LKLdRtO80XKBbjVhahKYFsMgY0TdpHOL8gS2UXDwR5g/4Pt12Avpi8WzfrZ/Z5vAQ/cab9MboOsL/4F8LSfPb/M6NrvBN7/H4Cb/iu+d+N+FGoX8Pd32gl5tssulOg19+V+VgMbzJ862rnm4e4HNnDGZBicvAf3fuy9IGMXb8gMQWwXcYgNjN4FznaDuADlGyAzBFNmPxfKfmc1APQATBpqeAZq6/T2x5DiH03F2v2346o3f9t5j/+mAszdGrjqCcA3/ag9QfXATpj3XwasXzC+gsnG/ewie105ibJdow+l42ff8w84/cC9+MWn7geO/j3wqXcA7/zn2x/snouxb5cd/n3r9d4GRYTdA137+VXufMj34xmf3I0H0QlchJN4AHvxFb4Yl+3P8NvXsz3uPRfa6Hz9gFutMu6DfKn9/4fnbHAxPGsvWNk6sGs/sGs/vnCK8H2v+3tsIUMODQXGGoZYwxC7MMQa5fY7hlBgnMUunOF17KFNHMRpaBgcxwF8lfdjDzZxIZ0CATiNdQw5w4V0GofoAZzm3fgKX4wHsBeHcBIX0SlsYA0neB8AxiX0VRyiU7if9+MePogNrJX73+QBNjGAAUHZClsoGGQwOECncTGdxBqGOMH7cAp7QGBoGAyQQ8PgAezFOy+4OHjsQ9k90Pj03afwLb9zCrvwW9iHc1iHLbfIocsvAwUGoNz/Yb8zqPKzJgPC+StUAxS4AGdxgM7gFO/GMb4QD2AvCHDbqm7Pbl/DQJH9nqEAATjD6ziNdRRoVvupUWAvNrGXzoFhG0Xl0MhZW+tG9z8Cribafa/+jonfGYQrDl+E9zc6omZ89vJn4+G3PRLr2MI6huWRjbDnUkYFtniAM1jHEJl7D+xFeoPXsIWs/H+WDY0C67SFAQpsIcMmD8AgZCigyCDnDLl7/wpoMAgaBTIYbCHDhlu/XscWcmj80YVXJDv2wcVX4/Gbv4kDdAa73GdpiAxbnGEI+2VANgENU34O7HdGAcIG1rDlrh/TGOUMeOL79Mcx5/kZCuzCFnbREBu8C6exji0M3CffjD6T7rOqxx5jKDIgMHK2/9sFdBYX0wPYhS1sYg1bnGEL9pq4hQxbbLPNh+gkDtED2OVG5cTuK/F7C41+PV6+5xWgE3dgyPZaso82sA/nsIkBTmM3MhR4CB3DZXQfzvA67sd+MAgX4SQuyb+Kh567G9cc+zBy1jiKQzjBF2APNrCXjtpzFMadlaNr2Brl2I+zOES2lM4w4QT24iTvxhay8vzeRUNchFN4LrnM4HvdQVeqDC5w92V/X4/K1d8MHLsFOPEle28+dotdlBSms+sA8LgXnP/4I78H+POfA276eZQztncFbPeSx7RwcOHsHtjPyKs+8Bk8ONvCc7Iv4LL3/FDSYyBeoRr1R137EH7Ta36i/J2hkA/2wmT78JjHPREHLjocZb/3nNzAZm5w5UUuDW8McOffACfvmv2iQ9cAlz0On7jzBB5z2QVlveQ8Pn33SVxx4Z7gC9SZzRw33X4c+USq8+EP2odHX3YgaFvTYGZ8+DPH8cC5JS67WJDD+3bhSQ+PHzzcdeIcPnrH/dH3s8o88sEX4BEP3p9sfw+cG+J/fub4yhoGtM2B3QN829ccTlJLD9jr0023H8fJjdW9PsXimsP78JjLF79HzOPTd5/E7Xd3oxsis4XB8AyGg/12NXYazMiGp/Co/efw0PXTdjHtmutdCSeQFwa33HUS1115MOGRV9g6Y8sh/cLn5ELo2AJptdxzxneT221unR4v9SWXmTDGPkdntvR43Z0jzLZMjo0tYSyzFYUrZayUzA5225V8NqPSvFPH7Kq+r4Lw2ZA6P/uMyYErgANXupKes3bhd1Y5uSmA4Tkcvf8EVLGBS3aTfW/NcKK0cTj6ebDbLpwefiSw70Etv5H1+OvP34d7Tm0gG57CgRO32ewBaRg1gKEMrLTNLpCCLjahzKZdBtTrMCoDcQFlchDn7udh+Xue7UGe7cN3fOu3foyZj0zb/0oFD0eOHOGbb76568MQBEEQBEEQhN5CRDODhx3htiQIgiAIgiAIwuJI8CAIgiAIgiAIQi2WOnggou8iotuJ6HNE9LKuj0cQBEEQBEEQdjJLGzwQkQbwawCeAeBRAJ5PRI/q9qgEQRAEQRAEYeeytMEDgCcA+Bwz/yMzbwF4K4BndnxMgiAIgiAIgrBjWebg4XIAd1Z+/7J7TBAEQRAEQRCEDljm4GGaAfh5vrJEdCMR3UxENx8/fjzBYQmCIAiCIAjCzmSZg4cvA7iy8vsVAM7rusbMr2PmI8x85PDhOE3gBEEQBEEQBEFY7uDhowCuJaKHEtEagOcB+KOOj0kQBEEQBEEQdiwz+rB3DzPnRPRSAO8HoAG8gZlv7fiwBEEQBEEQBGHHsrTBAwAw8/sAvK/r4xAEQRAEQRAEASDm8zTIvYWITgG4vevjWGIuBnBv1wex5MgYzUfGaD4yRtsj4zMfGaP5yBjNR8ZoPjJG03kIM08VEy915qEBtzPzka4PYlkhoptlfLZHxmg+MkbzkTHaHhmf+cgYzUfGaD4yRvORMQpnmQXTgiAIgiAIgiAsERI8CIIgCIIgCIJQi1ULHl7X9QEsOTI+85Exmo+M0XxkjLZHxmc+MkbzkTGaj4zRfGSMAlkpwbQgCIIgCIIgCPFYtcyDIAiCIAiCIAiR6FXwQESDro+hDxBRr97X1BCR7voYlh3X1V2YAREddN+p62NZVojoMvddxmgGRHQ1EU21QhQsRPQwInpy18exrBDR/q6PYdkholVzFu2cXkwyiWg/Ef1/AH6BiJ7Y9fEsI26MfoyILmBmIwHE+RDRPiJ6FYCfJaIndX08y4gbo9cAeDURPVUuuiP8JJiIfhLA+4noGmZmmRyPQ0R7iejVsGN0iKU29jyIaDcR/SqADwK4VhbGzsedR68B8BkAT3OPyWfN4e75rwHwNiJ6ARFd2vUxLRtujF4N4GeI6HFdH88qsfQTTHdR/S3YY/0sgJ8kohu7Parlgoi+CcBHAPw7AD/vHpYbdgUi+icA/haAgW0G81+I6Bu6ParlgoieA3se5QA+BuDVAB7W6UEtJxcAGAL4lwAgk+MR7nN2K4CzAJ7MzPd1fEjLyksAHATwSGb+K2Yedn1AywQRvQD2GnQ3gH8P4JsB+ax5iOjBAN4GYAvAbwJ4PoCruzymZYOILgHwFtgx+hyAf0VEL+72qFaHPqwqXgLgocz8PAAgorsAPJ2Ivo+Z/6jbQ1sa7gfwHwF8GMB7iehxzPx3RKSZuej42JYFA+CnmPmdAEBEjwfwZAAfJSKSmxIA4A4AL2LmjwAAET0TwK5Oj2i5IFfOdSFsYPW/E9F3MfOfyGetZAhAM/NPAgARPRzAMWY+1e1hLQ9EtAvAQwD8F2bOXRb0XgB3MPNWt0e3NNwP4AeY+RYiuhzA9UT0CGa+vesDWxIuAXAhM/84ABDR8wDI9WecywBcxMwvA8ryrh8ioi8w84e6PbT+s3SZByJ6JBH9MhE9j4jWmPnLAO4hon/qnvIXAG4B8NSdWus3MUYDd0F9NzMfBfAHsIEEdvJkpjJGP+hKb/4UwHsq5QEfB7AG7NzVrCnn0UeZ+SNE9GAi+msAXwvgZUT0JDfh2VFMnkPMbJh5E8AJAKcA3ATgOW5ys+PGB5h6vf4TAB8hot8mov8O4NcB/AERfTcRrXd8uJ0w5XO2CeBK2HPnpwC8CsB/AvAqIjrU6cF2xJTP2nuZ+Rb354thF39OdniInTLlHPp7AHuI6FeJ6G8BPBb2Wv1SIrqg48PthMkxAvBFAF8gome7p3wF9rr9DCLa19mBrghLFTwQ0f8G4K0AjgN4NoD/RkRXwabnvpmI9jPz/QA+6V7y4G6OtDumjNHriehSZt5wT/lNABe5lYgdycQYfT+A/wbgEDMPK+UBTwXwpY4OsXNmfNZ8zez9AN7IzI8A8OcAfhDAjirxmnIOvd4FVQrAw5j5A7D16t8Mm/F7GO0wndGUc+i3XZD5bwF8K4CPMfN3AngvgKcD2HE1x1PG6HfcxOWVAL4HwD5m/iYAr4AtF/yRro61K2Z81sr6fTdRvhrA9e75O/1z9nqyhg1PB/AF2M/Zo2HLu68F8H1dHWtXTDmHfgM2O/M+AD/v9EX/AXbBJwMwEP3MYizbh/BaALcz838G8CL32HfB1j2eAnCDe+yvAHwLlu/4UzBtjL7fr1i54OrXYGtqQUSPJ6IDXRxoh0yOkYItMbkIKNOXuwG83/3+6B24Kjo5RgR7Hh1m5i1m/g33vDcAeAx2noZm2vg8F8B+AH9PRG+CvTF9BVaLdSszm46OtSsmx6iAve58BcARZn6Ne96vAvj6To6we6aN0Qthy5TuBHAdADDzp2HH7avdHGanzLoWXVR5zptgr0OQzxkA4AUA7oE9n+4CAGb+Y9hs+tkOjrFrqmN0A4ABgG8H8Iew1+2PAHgqM/8S7JxS7dSKg7ZYtsn3lwB8lYiuZOZzsGKX62A/IB8A8EIiegqAr4O9yC7b8adgcox+D3aMHumfwMxvAbCPiM7BrgLuNGaN0de6v68DOArg24joJgAvxs47l2aN0bUTz/s62M/ficTH1zXTxufRAJ4AK3Q9AOD/APAdsOnxf9bVgXbItDF6LIBvZObqJPg6WNHiTjuHgPPH6M2w43EIwI8BuJqInkLWvOHZsFm/nca86zVgFy80sPMyD5g9Pk8A8HkA1xHRtUR0LWyQfqa7Q+2MaZ+zxwN4LDN/ipnfxMyn3PzxIwBOd3isK0EnH8JJrcJE+igH8AigjKQNgEcz85/C1s++ELau/7eZ+bY0R5yegDF6P4ANAEfc8/YS0a/Aijp/mJlfwMwPpDnqtDQYI1968y2wE78fBfAbzPx/M/NKrtY0HSMiegQRvR22DO71zHxrmiNOS+D4FLBC15cz8zOZ+eOw19BXMPPrEx1ycgLH6BxG59BVRPROAK8F8Aa5XgNOE7IF4EnM/DkAPw7gKbD3tl9h5j9IcsAd0PSe5rgNNlBf2cxDg8/Z18OWTn4atkznnbDn0PuTHHAHBH7OzsEGWCCiS9y16NUA3uN0R8ICJA8eiOhnAXyYbE+Cb3cPawBg5r8C8ACAJxLR17i/vRduVY+ZfwfA/8nMX8PMv5f2yNPRcIxe6P5+BsD7mfkaZn5r4kNPxiJjBOB2AD/OzE+TMTpvjF7gft4E8KfM/I3M/PspjzsVDcbnPbDXnw33es3MOTMfS33sqVjwc3YWwJ8w8xPlczY2Rv8D7nPGzO9m5p9h5m9Y1c8ZsPB5BGb+Y2ZeWc1Mw/H558x8jq2z2Y3M/Fj5nM2cFx0D8AfM/HhmfnviQ19JkgYPZL2bnwS76vtVAL9ERJeztavzHW3fClsS8G9dVHkpgA/4VOWqR4wNx+gyAH9GrqEXM7+3g0NPxiJjBADMfCsz/78dHHoyFhijPyciYuY7mPl1nRx8Aha4Fn3Qr3bxiruZLXgtUsx87yqfQ8BCY1Te01adRc+jTg46IQtciz5Uued/voNDT0ZL86K3dHDoKwvF1owQ0V63Gg4ieikAw8y/7n5/DYCHM/M/cTcb4x6/AsDLYFNQD4b1nv9Y1APtEBmj+cgYzUfGaHtkfOYjYzQfGaP5yBhtj4zPfGSMlhxmjvIF4CLYOs43A3gWbJbjXwF4y8TzvgLgKe7nrPI4wTaHi3aMXX/JGMkYyRjJ+CzDl4yRjJGMkYzPMnzJGPXjK0pKkIieC+unex+Ad8EKU58AK768noieUHn6L8JZsDJz7h9kyxdiHN8yIGM0Hxmj+cgYbY+Mz3xkjOYjYzQfGaPtkfGZj4xRf8gibffTAF7AtrkLiOgHAKtXIKKfg40qvZPCF2C90+FqrXeK966M0XxkjOYjY7Q9Mj7zkTGaj4zRfGSMtkfGZz4yRj1hYc3Ddm8a2S6RbwZwOYCPAXgbM7+LrGXWF2Cbvb0UwIeY+T8tdCBLjIzRfGSM5iNjtD0yPvORMZqPjNF8ZIy2R8ZnPjJGPYcXqHkCsF75mab9HcAPuZ+/Fzb19O0ALgbwA7AdWv/NIsew7F8yRjJGMkYyPsvwJWMkYyRjJOOzDF8yRv3/WuTNfwSA4wD+s/tdu+9qm9e8GcB3Vn7XXQ9A1MGVMZIxkjGS8VmCLxkjGSMZIxmfZfiSMVqNr0UE0wbAFwG8hIguZeaCiDIeWWZdVX2yE7pcASuEAbD6PumQMaqDjNF8ZIy2R8ZnPjJG85Exmo+M0fbI+MxHxmgFqK15cG9u7n4mAN8I4CoAjwfwOGZ+unv8KgCvAnAPgFfANu34FQAHAfwiM7+79f9iSZAxmo+M0XxkjLZHxmc+MkbzkTGaj4zR9sj4zEfGaDWZ67ZEtjvfLwAYENF7mPmDzMxEtBfA05j5R4joGBF9B4B/APBYALcz80+4128BeCszvyni/9EpMkbzkTGaj4zR9sj4zEfGaD4yRvORMdoeGZ/5yBitONvVNME22/h1AP8dti34B2B9dwcArgfww+55vw+bivqFidevfF2ajJGMkYyRjM8yfMkYyRjJGMn4LMOXjNHqf83LPOwHcB2ApzPzKSK6F1b5/j0AvgTg14noBvfmfxbWoxdEpGFbie+EujQZo/nIGM1Hxmh7ZHzmI2M0Hxmj+cgYbY+Mz3xkjFacbQXTzHwSwB0AXuQe+ktYz92nAdgH4G8A/C4zPxXACwH8P0Skmblg5npiip4jYzQfGaP5yBhtj4zPfGSM5iNjNB8Zo+2R8ZmPjNHqU6fD9LsAfBdZVfxRIroFwKMBbDLzDUDZ7ONv3eM7ERmj+cgYzUfGaHtkfOYjYzQfGaP5yBhtj4zPfGSMVpg6Vq1/AWuR9SIAYOabAXwTXOBBVkm/0yNFGaP5yBjNR8Zoe2R85iNjNB8Zo/nIGG2PjM98ZIxWmLnBAzMfBfBuAM8goucQ0dUANgAM3d//V3t3bIMwEARRdBzQFB1QAJ25XCRTATfrgADzXgWrn01wutc3D/wFGnUadRqt6dNp1GnUabSmT6fRtZ355+GR5JnknmQ/jmP/5mG/SKNOo06jNX06jTqNOo3W9Ok0uqbxeEiSbdtuSQ6L8TONOo06jdb06TTqNOo0WtOn0+h6To0HAADgf00eTAMAABgPAADAjPEAAACMGA8AAMCI8QAAAIwYDwAAwIjxAAAAjBgPAADAyBt6n3S5oPWErQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 936x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "predictions['FHMM']['Fridge'].head(300).plot(label=\"Pred\")\n",
    "gt['Fridge'].head(300).plot(label=\"GT\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comparing NILM algorithms (CO vs FHMM)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`nilmtk.utils.compute_rmse` is an extended of the following, handling both missing values and labels better:\n",
    "```python\n",
    "def compute_rmse(gt, pred):\n",
    "    from sklearn.metrics import mean_squared_error\n",
    "    rms_error = {}\n",
    "    for appliance in gt.columns:\n",
    "        rms_error[appliance] = np.sqrt(mean_squared_error(gt[appliance], pred[appliance]))\n",
    "    return pd.Series(rms_error)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "? nilmtk.utils.compute_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CO</th>\n",
       "      <th>FHMM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Sockets</th>\n",
       "      <td>28.268673</td>\n",
       "      <td>37.155416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fridge</th>\n",
       "      <td>107.893730</td>\n",
       "      <td>100.269828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Light</th>\n",
       "      <td>120.060822</td>\n",
       "      <td>73.627119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dish washer</th>\n",
       "      <td>456.985626</td>\n",
       "      <td>185.935940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Microwave</th>\n",
       "      <td>235.265549</td>\n",
       "      <td>545.966517</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     CO        FHMM\n",
       "Sockets       28.268673   37.155416\n",
       "Fridge       107.893730  100.269828\n",
       "Light        120.060822   73.627119\n",
       "Dish washer  456.985626  185.935940\n",
       "Microwave    235.265549  545.966517"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmse = {}\n",
    "for clf_name in classifiers.keys():\n",
    "    rmse[clf_name] = nilmtk.utils.compute_rmse(gt, predictions[clf_name])\n",
    "\n",
    "rmse = pd.DataFrame(rmse)\n",
    "rmse"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
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    "name": "ipython",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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